Travelers inevitably make multi-modal route choices ? a combination of modes making a trip. It is particularly important in the analysis of inter-regional travels, including access modes, trunk modes, egress modes etc. The paper focuses on the mode choice behavior in the entire trip covering each part of the trip. This paper also aims to give contributions to the evaluation of the policies aiming to more efficient and smooth transfer between travel modes. An advanced discrete choice model called "Multi-Nested GEV (MN-GEV) Model" is formulated to capture the correlations among the elements of the inter-modal travel behaviors. The stability of MN-GEV model parameters is also examined to show the capability of the model. It is applied for the inter-regional travel survey data of Japan and the estimation results are compared with other types of discrete choice models.

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This paper is aimed to propose a new framework and methodology to incorporate service quality and inertia effect into stated preference model. We use structure equation model and stated preference method to conduct with psychological and quantitative attributes. The logistics regression is used to generalize inertia effect and to explore casual influences of important factors on inertia effect. The empirical data is focus on the choice behavior of intercity bus transport. The computer questionnaire is based on the each traveler's experiences in RP choice to design the corresponding SP scenario in avoiding to the response bias. The results of logistics regression show that there are significant casual influences between inertia index and number of alternative, traveling frequency, and personal income. The estimating results of MNL model prove that the specification of generalizing inertia index has the better model fitness than the traditional 0-1 inertia index.

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In this research, first, we categorized transport surveys of passenger flow in Japan and found out their situations. Largescale transport statistic surveys have been conducted and they provide information for planning or just for statistics purposes. Next, we analyze current situations of urban transport using the results from Nationwide PT Survey, and found the following. a)The number of trips has declined in Japanese cities as the society ages. The vehicle ownership and driver license holders increased farther. Thus, automobile use has increased overall. This could exacerbate environmental burdens in the future. b)Compared to younger age groups, the elderly use car less often and makes fewer trips. As aging progresses, the number of elderly without mobility is anticipated to increase. c)In Japanese cities, modal split varies by the size of urban area and population density. Lately, with the declining trend of population density, it may contribute significant increase in car use.

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This study proposes a methodology for estimating places where people may perform additional activities with utilizing the concept of space-time prism. Decision about travel behaviour can be affected by time constraints of their life and spatial structure where they live. Considering such constraints is important to estimate which place is likely to be chosen for the additional activities. This study develops a method to estimating the place which people may choose as an additional destination. This method proposes the concept of path constrained potential path area (P-PPA) by incorporating the concept of space-time prism with information of revealed trip trajectories which can be taken by position detection tools such as GPS and so on. An efficient calculation algorithm with considering actual network structure is proposed. An empirical test has been carried out in the real network to check the proposed methodology.

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A travel cost function is critical in traffic assignment in that the route choice behaviors of users could be described by the function. Parameter calibration of the function is to adjust parameters in a model so as to represent local traffic conditions. In order to describe correctly the real travel patterns in the model, we should calibrate the parameters by observed information. This paper presents a calibration method for travel cost function, which widely used in traffic assignment. It is based on bi-level programming such that the upper level is to minimize the difference between observed link flows and estimated ones computed from traffic assignment, while the lower is to describe the route choice behaviors of users on the transportation network. A solution algorithm will be given and through a numerical example it is also shown that multiple solutions is existed in such problem.

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Confronted with rapid urban growth in developing cities, it is expected that configurations of transportation network, as well as their operation conditions, could have significant impacts on various aspects of trip-making behavior. Meanwhile, trip-making behavior is one of the most important determinants during the design and management process of transportation network. To properly reflect such interdependency mechanism, this paper first attempts to establish a travel demand prediction model with feedback for the Jabodetabek metropolitan area, Indonesia. Compared to the traditional four-step model without feedback, it is empirically confirmed that introduction of feedback mechanisms could improve the model accuracy a lot. Based on the estimation results of the feedback model, some urban and transport development policies are evaluated from the perspective of realizing environmentally sustainable cities.

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Passengers choose the mode and path of public transport for their daily trip according to the different individual demands. The typical factors are like fare condition and trip time etc. But, the condition of comfort for passenger becomes an important factor now. At present, the applied modeling softwares begins to take account into aspect of comfort; however it still stays the beginning now. Effectively, passengers can choose the mode of public transport according to their different comfortable level. The goal of studying aims to create a new algorithm of comfort of passengers in order to reinforce the missing aspects in the actual software. The first part of the report consists in presentation a longitude aspect of comfort. In the second part has to establish a mathematical algorithm model according to the aspect of comfort defined, and then codified a calculating program by Scilab for algorithm inducted. Finally, we will give a simple numerical case to display these relations between the trip cost and the comfort of passenger.

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This paper formulates a model to explore market shares of intercity modes including automobile highway (AH), high-speed rail(HSR) and air transport(AT).The relationship among demand-supply attributes such as fare,speed,terminal locations,travelers' trip length,the value of time,departure time and origin and destination locations is explored to identify market boundaries by comparing different routing strategies for each type of passenger.Passengers' optimal choices are assumed by minimizing their generalized travel time and then are aggregated by accumulating a probability density function of value of time and time zones with the same waiting time differences.The results show that passengers with higher value of time tend to choose the mode with less travel time but higher cost. And how demand-supply attributes such as the number of persons in one car, access time to HSR station, and HSR fare impact market share distribution among three modes.

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Unreliable transport systems cause variability of route travel time and lead to different route choice behaviours among three harbour crossings in Hong Kong. This paper conducts a comprehensive investigation of route choice behaviours over a series of consecutive days. Data analyses of route choice behaviours are based on one-month Automatic Vehicle Identification data which are collected from Autotoll transponders at toll plazas of three harbour-crossing tunnels. The results of the analyses show that the route choice behaviours vary significantly between commercial vehicles and private cars as well as spatial-temporal contexts. It was also found that the split of traffic flows among the three harbour crossings is not well balanced by time of day and day of week. Thus there is a need to consider differential tolling (i.e. tolling by time of day) by revamping the tolling arrangements of the three harbour-crossing tunnels traversing the Victoria Harbour in Hong Kong.

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It is expected that vehicle holding durations differ substantially across households. Some households may keep their vehicles as long as possible, while others may replace some of their vehicles after holding several years. Even though existing studies have incorporated such heterogeneity using duration models, one-peak distribution is usually assumed. In reality, this assumption can be easily violated. In this sense, the heterogeneity of duration distributions has not been satisfactorily represented in existing literature. To represent the heterogeneity in the household vehicle holding duration, the paper proposes to apply a latent class modeling approach to simultaneously incorporate different duration distributions. Such modeling approach could deal with multi-peak distribution of vehicle holding duration. Using a data collected in several Japanese cities in 2006, this paper confirms the model effectiveness from both model performance and applicability. It is found that household characteristics are important factors to explain the latent classes.

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Commuting travel is the main source of the traffic congestion in the peak period, and telecommuting is considered as one of alternative strategies to reduce commuting travel. This study develops a logit model to analyze individual choices between telecommuting and commuting. We use stated preference survey data collected from 349 households of Taipei city to calibrate the model. Individual socioeconomic characteristics, time saved and trip chain behaviors are found to be significant factors. Compared with the activity use pattern for saved time before and after adopting telecommuting demonstrates that some activities would be shifted to off-peak period, while some would be conducted at other places, some would be accomplished by other people, and some would not change. The results show that telecommuting may result in the various spatial patterns of activities, changes in family roles, more discretionary time for individuals, and the reduced traffic in the peak period.

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This paper investigates freight forwarders' perceived satisfaction on service attributes of ocean carriers and their choice behaviors. The mail surveys were conducted to freight forwarders, providing services between the United States and Taiwan. This research employs factor analysis to combine a large number of service attributes into few latent factors and the multinomial logit model to examine ocean carrier choice by freight forwarders. The result of factor analysis obtained three factors, namely speed/reliability, safety/empathy and convenience. The estimation results of the multinomial logit model reveal that transit time, frequency of sailing, record of cargo delay, freight rate and latent service quality factors are the significant variables influencing the choice of ocean carriers. Freight forwarders are sensitive to the changes in service frequency and transit time, indicated by the values of direct elasticities. The findings provide useful insights into ocean carrier choice behaviors by forwarders.

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Recently, various retail shops are installed in the railway stations in the Tokyo Metropolitan Area. Many passengers enjoy shopping and window-shopping while transferring trains, and waiting in the station. Such passenger behavior causes issues such as crossing of the passengers's flow and the decline in walking speed. Therefore, it is important to consider such behavioral patterns in the planning and management of facilities in the railway station. Pedestrian simulation model is a powerful analytical tool for determining optimal layout of facilities. So far, many pedestrian simulation models have been developed. These models can reproduce the average walking speed, and sectional pedestrian volume. However, these models do not consider behavioral patterns in visiting the facilities into consideration. For developing the pedestrian simulation model applicable also to the facilities arrangement planning, the study conducts a basis analysis aimed to grasp passengers? visitation patterns of facilities in the railway station.

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Multinomial logit (MNL) models are developed to identify important factors affecting the selection of similar bundles of expensive physical damage coverage for new cars. Nested logit (NL) models are further developed to elucidate the choice behaviors for such highly similar auto insurance policy (AIP) bundles. A four-year panel data with 9,949 voluntary automobile insurance records, randomly drawn from a non-life insurance company in Taiwan, are used to test the empirical case. The estimation results of the preferred MNL model show that age,engine capacity and imported/domestic vehicle are significant factors influencing one's selection of AIPs.The NL models further confirm that the inertia of the same individuals tend to repeat buying the same physical damage coverage policies for consecutive few years.

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Public transportation (PT) plays a major role in order to meet the ever-increasing travel demand in developing cities. With urbanization trend at the fringes of the region, away from the city core, travelers must take different modes or to chain trips to reach their final destination. This study investigates the travelers? decisions on choice of mode and modal combination patterns through modeling tools. Specifically, it looks into the travelers? preferences for different modes in performing PT chains. Empirical analysis using logit-based extreme value models such as multinomial logit (MNL), and nested-logit (NL) was performed. It introduces the applicability of cross-nested logit (CNL) model structure in analyzing PT mode choice behavior. Utilizing variables such as total travel time and cost, with some socioeconomic variables, for all model formulations, estimation results point to the flexibility of more advanced models in dealing with the choice situations involving PT chains.

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In case of Car-LRT, in-vehicle travel time was found to be the main cause of shifting in modal choice from car to LRT while other modes are not as much impacted by the same, so if in-vehicle travel time were reduced through enhanced punctuality in the future, potential transport demand for LRT brought about by conversion from the demand for cars would exist. In cases of Bus-LRT and Taxi-LRT, out-of-vehicle travel time was responded to be the major cause of shifting in modal choice, so should waiting and transfer times be made long on account of bad punctuality, the competitiveness of the new transport system is deemed to be very little. For the trip case(2), where transfer should be made and with cars, variation of in-vehicle travel time appears to be in important play where improvement of punctuality and intermodal connection measures are deemed required.

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This study focuses on the trip generation characteristics of business process outsourcing companies in the Philippines. Business process outsourcing is a rapidly growing industry and as such, has spawned land use that has significant differences in trip generation characteristics from traditional offices. Travel demand characteristics for BPOs, for example, are quite different because of the unusual nature of operation of such companies due to the varying times in countries served by employees. Many BPOs were initially located in central business districts in Philippine cities. However, as the demand for BPOs continue to increase, offices have been established away from the urban areas at business and industrial parks. The paper examines the characteristics of BPO trip generation. It presents the formulation of strategies to address problems pertaining to transport demand as well as the provision of facilities to accommodate the continued growth of the industry.

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The development of techniques for calibrating the trip distribution models from traffic volumes to obtain the O-D matrices is well advanced. Therefore, positive results on this development will be further developed by combining trip distribution and mode choice model (TDMC) and calibrating it using low cost traffic (passenger) volumes information (see Tamin 1997; Tamin and Purwanti, O 2002). As usual, the traffic (passenger) counts are expressed as a function of model form and relevant parameters. In this case , the TDMC model is represented by a function of a model formand relevant parameters. The previous research still in a burden condition of All or Nothing which is not realistic for some road network in urban area. So, the main objective of this research is the application of a combined trip distribution-mode choice model estimated from traffic count under equilibrium condition.

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This paper aims to develop alternative forms of emergency trip destination (emergency shelter) and investigate the evacuee behaviors affecting the shelter choices for future tsunamis and other disasters.The shelter allocation forms are developed using the logistic regression model and neural network model in estimating the probability of evacuee choice of selecting evacuation destinations between public and private shelters.

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In Asia, many developing countries are facing the issue whether to develop the motorcycle market as a transitional phase or to jump to the automobile market directly. In order to examine the issue, this study attempts to develop a mixed discrete/continuous demand model to analyze the characteristics of household's decision behavior associated with the mode to work, ownership and usage of cars, and ownership and usage of motorcycles. Empirical analyses indicate that it is not easy to suppress the ownership levels of motorized vehicles by adopting price mechanism or by improving the quality of public transportation. Thus, in order to prevent a great deal of problems resulting from mixing car and motorcycle flows, we suggest that it is better for developing countries not to approve the development of motorcycles as a transitional phase.

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This study aims to find the comparability between Japan and Taiwan by examining their long-term growth patterns of aggregate travel demands from 1967 to 2004. It is found that travelers both in Japan and in Taiwan see bus as inferior goods, and passenger car ownership and domestic air as more luxurious than rail and bus. Nevertheless, a number of differences between Japan and Taiwan are even more noticeable. First, travelers in Taiwan see public transportation as inferior goods, and rely more on private transportation, while travelers in Japan rely on both private and public transportation. Second, to travelers in Taiwan, passenger car is luxurious goods, while to those in Japan, it is necessity goods. Third, in Japan the private mode (car and motorcycle) ownership demand demonstrates overall substitutive effect, instead of complementary one, with public transportation, while in Taiwan no such evidence is found.

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Based on the travel psychology of citizens, this article considered about the six indices of being safe, comfortable, swift, convenient, in-time and economic comprehensively, analyzed the relationship between these indices and then built up an evaluation index system. Then using fuzzy evaluation model and multi-objective decision making method, it researched on citizens' traveling behavior, built a mathematic model and thus located comparatively scientifically the traveling modes citizens adopt. With live examples of citizens of a district, this article proved that the model is simple and practical, could be applied to practice basically.

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Forecasting demand by taking into considerations the present international air cargo market and its possible change in the future trend will assist in the construction for civil aviation policy and the planning of international airports. When forecasting air cargo volumes, due to the fact that uncertainty factors often cause deviation in estimations derived from traditional linear regression analysis, fuzzy regression analysis has been adopted to amalgamate with linear regression analysis, for reducing the residual resulted from uncertain factors. In this study, relative researches were presented to indicate the factors influencing export air cargo volume. Stepwise regression was implemented to find out key variable factors that had major impact on Taiwan air cargo export and import volume. In addition, fuzzy regression analysis and volatility concept were applied to accurately forecast the demand for Taiwan air cargo volumes under present scenario.

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Many past researches have invoked time, cost and specific mode attributes to explain transportation mode choice. Alternatively,this paper attempts to study an additional dimension by incorporating latent factors. The general structure comprises two models, namely a latent variable model and a discrete choice model. The estimation is performed by first determining the significance of specific latent variables: safety, comfort, convenience and flexibility. In the second stage, the discrete choice model is estimated by integrating the choice and the latent variable in the choice process. The discrete choice model is estimated via logit and probit regressions. The main findings are that the latent factors are statistically significant and thus enrich the discrete choice model. By providing better explanation to mode choice behaviour, the enriched discrete choice model could prove useful to policy makers in managing transportation infrastructure and services to maximize welfare.

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New Zealand has a long and continuous history of transportation planning, with the first study using a model undertaken in Christchurch in 1959. Over the years since then, every city in New Zealand has had at least one study, and many have had regular reviews. The technology used in the models has also developed without pause, with the result that the techniques now being used are equivalent, or ahead of those in the rest of the world. The paper describes the development of models in New Zealand, touching on inputs, data sources, technology and outputs. It concludes with a brief comment on the new generation of models which are now emerging.

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This paper investigates the modeling framework and the existing available data which could be used to develop the activity based travel demand model in Bangkok. The paper focuses on two main issues including “the population synthesizer” and “the activity generator”. It is found that there are possibilities to create the activity based model by using the existing available data from several sources. However, the modifications of the existing modeling framework from previous activity based modeling researches are needed in order to match the existing available data.

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Mode choice methods model the traveler’s choice among a set of alternative mode of travels. This study proposed the Fuzzy extension of the Analytic Network Process (FANP) to model the travel mode choice. Fuzzy set theory could be incorporated in the Analytic Network Process (ANP), which is a widely acceptable decision making tool in order to capture vagueness of the human decision. Triangular fuzzy numbers and their degree of fuzziness are used to express human judgment that is articulated in natural language. The method presented in this paper utilized the alpha cut and optimism index to transform the fuzzy comparative judgment matrix into sets of crisp matrices. The proposed method can be an alternative to conventional mode choice modeling techniques that are used to model travel mode choice problems.

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The paper examines commuting bahvior to employment sub-centers in metropolitan regions. Traffic analysis zones are arranged in order of employment density to identify discrete clusters of similar characteristics. For each employment zone an employment location specific prefrence function for the journey to work is constructed. This allows comarison of the spatial extent of each employment center labor market. The mean trip length for the commute to each employment center is explained by the parameters of the quadratic function that describes the prefrence function. Results are presented for the city of Sapporo, Japan, where the models were calibrated on data for 1972, 1983 and 1994. Growth in population and employment with a polycetric employment formation in the suburbs has led to an increase in the region's mean trip length.

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The development of combined trip generation, trip distribution, mode choice and route choice to obtain the O-D matrices is well advanced. Therefore, positive results on this development will be further developed by combining each part of four step models. The previous research represents combination from sub-models series in which each series must be done separately and successively as well. With this combination model, modeling process become shorter and faster thus the result is comply with each phase of expectation. Besides, consistency between the model phases which were combined can be more guaranteed, due to the definition and input were utilized the same materials in the models.

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This study investigates the vehicle routes for a firm with its own delivery fleets and a single depot. A mathematical programming approach is employed to construct a vehicle routing model for handling mixed pickup and delivery operations by referring to the Vehicle Routing Problem with Pickup and Delivery (VRPPD). Furthermore, this study utilizes a heuristic algorithm to develop a problem-solving procedure. A revised Nearest Neighbor (NN) method is developed to obtain an initial solution. The 2-Opt exchange and Simulated Annealing (SA) method are adopted to develop the solution-improving procedure. Analytical results of this study are the optimal sequence of vehicle routes and the customer sets served by each vehicle. A sensitivity analysis among vehicle capacity, travel distance and number of routes is also proposed.

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As recent skyrocketing prices for crude oil have impacted the development of airfreight industry, operating environment becomes increasingly harsh, while increasing service quality and competitiveness are pressing issues for management. This paper will employ quality function deployment to integrate inside quality technology and outside consumer voice and through the use of the house of quality illustrate the company's performance in terms of service and offer suggestions for improvement. As the conclusion shows, in terms of outside consumer voice, the three main factors demanding improvement and three most factors in greatest need of improvement with regard to quality technology.

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This paper mainly discussed the operation models of supply chain for notebook-computer manufacturers in Taiwan. To Explore and analyze the key factors emphasized by different operation model. The operation models of supply chain mainly included the business model (OEM/ODM) and the process model (BTF/BTO/CTO). For understanding the particular characteristics within different operation models, 12 notebook-computer companies located in Taiwan were investigated by means of the questionnaire and depth-interview. Grey Relational Analysis method was used to find the key factors among different operation models (six models combined with different type of business model and process model). According to the result, different operation models emphasized the different factors with relation to the characteristics and operation targets.

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Convenience stores in Taiwan have made remarkable successes with retail delivery services by integrating E-commerce and logistics systems to form a new retail delivery model: "On-line shopping with pick-ups at convenience stores." The main purpose of this study is to explore what kind of factors can influence the pick-up point choice behavior by using a catastrophe model. In this paper, the catastrophe characteristic of the choice behavior has been discussed and used by cusp catastrophe model that is based on the empirical data. The outcome has shown that these characteristics include bimodality, hysteresis, and catastrophe are present in the research data. When increasing the value of the retail delivery services through some marketing strategies, the loyalty relationship between customer and convenient stores will be enhanced.

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This paper presents multi-agent models for evaluating the behaviour and interaction among stakeholders who are involved in urban freight transport systems as well as effects of city logistics measures. Multi-agent simulation on a small test road network demonstrated that the VRPTW-D model which dynamically adjusted vehicle routing planning to the current travel times generated good performance in terms of increasing profits for freight carriers and decreasing costs for shippers. After applying multi-agent models on a large test road network, it was observed that introducing the VRPTW-D model generated a win-win situation by increasing profits for freight carriers and decreasing the costs for shippers. The results also show that the implementation of road pricing can reduce NOx emissions but may increase the costs for shippers. To avoid such effects, introducing co-operative freight transport systems helps shippers to reduce their costs.

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This paper presented a method to construct an integrated transport network model after analyzing the characteristic and structure of the network and the path choice behavior between the origin and destination. First, the conception of integrated transport network is given and meanings of dummy links in the network and its constructing method are discussed. Three kinds of dummy links for building the integrated network model, namely the attributes based dummy link, urban road sub-network based dummy link and the multi-scale based one, are developed. And then three kinds of network models are constructed with different dummy links for Chinese Northeast region, and the performances of them are evaluated and compared.

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This study establishes a discrete process-interaction simulation model to solve cold chain home delivery peak-demand problem at operation center. We simulate its ceiling capacity and use it to evaluate alternatives to over-capacity. A Penghu case study shows that current capacity is around 360 packages under five members/vehicle assignments. However, capacity can be increased to 435 once staff's operation efficiency was increased by 20% (i.e., decreased by 20% operation time for each job-item). In case of over-capacity or trucking delay, dropping out unnecessary job-items such as cargo number and weight recording is a workable option to save operation time. In addition, depending on package amount, truck's arrival delay at operation center is acceptable for fleet control. For example, a late arrival truck with 30% (of 361 units) packages carried, a delay of thirty minutes is allowable. At 79%, only five minutes is allowable.

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The design of a logistics system can be defined as a Location Routing Problem (LRP), which is to find the optimal number and locations of the distribution centers, simultaneously with the vehicle routing to minimize the total system cost. In this research, a three-phase hybrid heuristic approach (LH-SA), combining the Lagrangian heuristic (LH) and simulated annealing (SA), is developed to solve the multi-depot location routing problem (MDLRP). Firstly, the LH is applied to determine the facility location set and the allocation of customers. Then an independent vehicle routing problem (VRP) for each selected facility location is solved by SA. Finally, the SA is used to perform a global search for all routing moves. The performance of the proposed algorithm is tested on two different groups of benchmark instances and compared with other algorithms in the literature. The results show that the LH-SA is competitive and updates 20 best-known solutions.

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Recently, a set of probe equipment comprising the GPS and an information terminal is increasingly mounted on vehicles to gather data on their operations. This study aims to better understand cargo deliveries over a middle/long-distance and within a city, using the probe data of trucks linked with the drivers' operation status. It is learned that truck drivers are constantly under psychological pressure to make the designated delivery time, which is getting more demanding in recent years. In this study, we estimate safety margin against the designated arrival time based on the probability of being late calculated from the truck's travel data. This is because the probability gives us an objective way to evaluate the risk of getting late. As this safety margin lessens the driver's psychological pressure for sticking to the delivery schedule, it is expected to greatly contribute to safety drive while improving the efficiency of deliveries.

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City cooperative freight transportation system is considered as an effective way to solve traffic problems. However, cooperation problems remain on the stage. With this in mind, this paper applies some important concepts in a cooperative game theory with focuses on core and e-core to analyze cooperation among members of an alliance of truck-focused logistics companies, which will involve 1 Providing a detailed and systematic standards of essence to judge the rationality of alliance formation by core; 2 Seeking rational payoff for partner companies and optimal subsidies given by public sector as to formation of an urban cooperative alliance by e-core; 3 Illustrating the crucial factors for promoting alliance formation and 4 Suggesting practical measures on how to make practical measures in order to boost cooperative alliance easily. This paper aims to enhance the understanding of interagency cooperation and decision-making behaviors facing truck logistics companies and local public sectors.

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Insufficient numbers of parking space and lack of (off) loading areas are some of common problems that driver of delivery trucks have to deal with. One way to address this problem is by increasing the utilization rate of the limited parking spaces by ensuring short parking time of trucks. Attaining this brief parking time, however, requires a shift from a traditional way of delivering goods to a policy-driven method. Traditional way presents a situation where the driver has to leave his truck and make his way to the floor of the building to make delivery. Although this method remains to be popular due to its simplicity, there exist methods that when carefully enforce would present sizeable benefits. One of these policies is by assigning workers inside the building to facilitate the (un)loading activities to free the driver immediately. This paper discusses implementation of cooperative delivery system and tries to produce a guideline regarding what CDS design is suitable depending on the characteristics of the CBD.

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This paper focuses on strategic planning in developing countries, particularly in freight transport network design and terminal development. Optimal set of transport projects is determined using a transport network design model with some objective function, which can be a single objective function or a multi-objective function. The model involves a bi-level modelling approach, where multimodal multi-user assignment is incorporated in the lower level problem and the combination of transport interventions or projects is optimized in the upper level problem. Application of the model is undertaken using data from the two archipelagic countries of Indonesia and the Philippines - both countries that would surely benefit from a multimodal transport design.

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Marshalling yards serve as switching and transshipment points in rail networks. The selection of optimal marshalling yard location influences not only total costs and delays but also economies of scale due to the consolidation of flows. The purpose of this paper is to develop an optimal marshalling yard location model considering economies of scale due to the consolidation of flows. This model also includes several cost components and capacity constraints related to rail networks. Test results are presented for rail freight transportation problems with 25 origins/destinations. Computational results are compared with recently published studies. We conclude that the proposed model can be used in the several decisions making on the improvement of the efficiency in rail networks.

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This paper discusses how to integrate forward and reverse logistics to decrease the total cost of third party logistics service providers. A mathematic model is provided without the assumption of straight-line distance. Demand for product and return amount of product can vary randomly in this model. We also allow that the demand of customers can exceed the capacity of their suppliers. Then we develop a Genetic Algorithm to solve this NP-hard problem and discuss its convergence. At last a numerical example is available.

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Given the high level of complexity and wide application of the vehicle routing problem (VRP), numerous solution algorithms have been developed for the past several decades, including many recent meta-heuristic algorithms with great success and popularity. In order to balance computational load and solution quality and to address the issue of flexibility and simplicity, this study developed a heuristic algorithm based on several classical mathematical programming techniques. The VRP is first formulated in the form of the set covering problem (SCP), and the Lagrangian relaxation is used as the backbone in designing the iterative algorithm. In addition, a concept similar to column generation is used to maintain a partial set of potential routes to reduce computational load. Based on the numerical experiment, the solution quality of the heuristic algorithm is stable. The result suggests that the solution algorithm should be able to deal with the operational problems arising from a highly dynamic environment.

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Logistics is one of the most important parts in supply chain management. More and more distribution centers have been established to provide the flexibility of supply. Major daily operation issues in distribution centers are routes and schedules of trucks. The dynamic vehicle routing problems (DVRP) are extension of vehicle routing problems in order to consider possible variations of travel times in the network. In this research, a two-stage framework for solving DVRP is proposed. In the first stage, the sweep method is conducted in vehicle assignment. In the second stage, a tabu search algorithm is implemented to improve routes under real-time information. The heuristic approach is then applied in an evaluation framework which assigning and routing operations could be simulated in a realistic traffic environment. The simulation-assignment model DynaTAIWAN is applied to evaluate assigning and routing strategies in a traffic network. Numerical experiments are conducted in Taichung City.

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Until now, the authors have been developing a model for international container cargo simulation (MICCS) which can produce the movement of the cargo with the volume of OD container cargo as a given input, focused in East Asian region, in order to simulate and evaluate international freight transport policy. This paper aims to evaluate the effects of the policies on port investment in China, using the model with two cross-sectional data in different years. The outputs of the model, incorporating with initial condition of transport environment in 1998 and OD container volume in 2003, are compared between cases with and without port investments during these five years in China. By this, it will become clear how degree these policies contribute to the increases of the volume handled in Chinese ports.

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This study estimates light and heavy truck origin-destination (OD) matrices based on the commodity flows in the Tokyo metropolitan area. There are three major concepts in this study. First, the truck OD is estimated using the commodity approach because it can reveal the important characteristics of the shipments. Second, the ability to estimate both loaded and empty trips is the main contribution of the model. Finally, loaded trips are mainly concentrated and modeled with trip chains behavior and shipment characteristics such as average payload, adjacent zones, and others that provide the most attractive zones traveled by trucks. The performance of the model is demonstrated using the relative mean absolute error between the estimated and observed truck OD matrices. The numerical analysis based on the light product of the food industry demonstrates that the proposed concept with trip chain behavior always outperforms the model without trip chain behavior.

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This paper examines Japan's growing international air cargo. This paper aims to analyze the its trend and by making use of two sets of Air Cargo Data made available by the Japanese Government, one from the Bureau of Customs Ministry of Finance and another from the Department of Aviation Ministry of Transportation. This paper also applies traditional four-step modeling process combined with commodity based demand analysis for the process of forecasting its demand. A regression model was generated from the first set of data to be used as the generation and attraction model for the demand forecasting. An airport choice model was estimated to distribute the future cargoes to the chosen four airports of Japan in preparation for the case scenario study. Lastly a sensitivity analysis of the model was performed.

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This paper proposes two ant colony system (ACS) based approaches, called stepwise-ACS (SACS) and cheapest-insertion-stepwise-ACS (CISACS), to solve the air-express courier's routing problem. The courier visits N predetermined delivery points and M pickup requests during the en route delivery. The SACS performs an ACS to obtain the initial tour for the N delivery points and then to find the shortest Hamiltonian path, in a stepwise manner, when the M requests arrive. The CISACS, following the SACS, incorporates the cheapest insertion into the SACS as new requests become known. Experiments with various pickup emergence patterns that characterize the real-world circumstances are tested for the proposed algorithms. The computational results, in terms of total traveled distance, are compared with the baseline results by a cheapest insertion (CI) heuristic. The results show that both SACS and CISACS perform better than the CI heuristic and that CISACS yields the lowest traveled distance.

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This paper presents an integrated microscopic simulation model that would be applicable for examining potential emissions impacts of truck-involved transportation policies in urban freeway system. Basic idea of the model is to integrate an emission model into existing microscopic traffic simulation framework. Considering truck-only lane policies, the effectiveness and applicability of the integrated model was evaluated with an application to the Long Beach freeway (I-710), a main corridor for freight transportation that provides regional access to the Ports of Long Beach and Los Angeles in the United States. The case study shows that the proposed model is useful in that when considering alternative policies of truck-only lane, it enables transportation planners to evaluate potential emissions impacts and traffic conditions simultaneously without real implementation of each alternative.

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