There has been a well discussed gap between theory and practice in the area of planning and scheduling of dynamic situations such as open job shops. In this paper a number of heuristics and concepts for how to address part of the gap are summarized and discussed. The heuristics and algorithms focus on dynamic and adaptive risk control related to work assignment and work sequencing. A theme connecting the heuristics is that of Aversion Dynamics - the desire to schedule and plan to avoid or minimize perceived problems. We will present the summary of research results on Aversion Dynamics followed by suggestions for further research focusing on risk management.

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Supply chain scheduling is a new emerging area of research. We study batch arrival scheduling problems at the manufacturer in a multi-level customer-centric supply chain, where promised job due dates are considered constraints which must be satisfied. We analyze the tradeoff between inventory holding costs and batch delivery costs. We show that the problems are closely related to batch scheduling problems on a single machine with flow-time related objectives. We prove that minimizing the sum of total weighted flow time and delivery costs is strongly NP-hard. For the unweighted version of the problem, we present efficient solution algorithms both for single machine and assembly systems. We also develop a dynamic programming solution for minimizing the sum of maximum flow time and delivery costs.

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There are a large number of multi-stage job-shop processes in production plants. Steel making process is also modeled as of a multi-stage job-shop process with crane handling. In the steel making process if there are two or more overhead traveling cranes for material handling in a house, it becomes very difficult to obtain in practice an optimal or near optimal solution under consideration of restrictions concerning crane interference caused between them as well as many restrictions for each facility in the house of production plant. In this paper, we first present a formulation of the scheduling problem taking account of the crane interference and then propose a heuristic algorithm to find a sub-optimal solution which starts at feasible solutions and solves the problem in a finite time. The algorithm is characterized by restricting search space and using hybrid method of depth-first search and width-first search on an enumeration tree for crane assignment. We also discuss an availability of this algorithm using a numerical simulation for a practical steel making process.

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This paper treats with an automated material handling system called a permutation circulation-type vehicle routing system (denoted PCVRS). In the PCVRS a fleet of vehicles unidirectionally and repeatedly circulate on a single loop to carry items to stations located along by the loop where items are served. No passing is allowed between vehicles on the loop. This may induce interferences or blocking between vehicles which may deteriorate the performance of the PCVRS. One of the most serious interferences is the one lap behind (denoted OLB) interference which occurs when the first vehicle is interfered by the last vehicle in a fleet of vehicles. Once the OLB interference occurs, the system can not reach the steady state in which no interference occur. This paper theoretically analyzes the steady state with no interference and the transient state with interferences including the OLB one. This paper considers both the infinite acceleration and deceleration and the finite ones on the vehicles, and four vehicle routing rules by which each job (and each vehicle) is allocated to a processing station for service. Two of them are existing ones and the other two are newly introduced to improve the existing ones. This paper adopts the throughput and the mean interference time for evaluating the vehicle routing rules. This paper confirms the theoretically obtained results by means of numerical simulation.

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The paper considers a sequential inspection policy in an imperfect production process which shifts randomly from an 'in-control' state to an 'out-of-control' state following a general probability distribution. Two different inspection policies are adopted in the proposed model: (i) no action is taken in the intermediate of a production run unless the process is found in an 'out-of-control' state by inspection and (ii) preventive repair action is undertaken once the 'in-control' state of the process is detected by inspection. The manufacturer is in a contractual agreement with the customer to provide free minimal repair service until a certain (warranty) period from the time of initial purchase. The objective is to determine the optimal number of inspections and inspection time sequence during a production run which minimize the manufacturer's future expected costs in present term or average cost in distant future. The proposed model is formulated under discounted as well as long-run average cost criteria and some structural properties on the optimal inspection policy are derived analytically. For a numerical example, the optimal inspection policy is determined and several managerial insights are investigated.

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This paper proposes an alternative data envelopment analysis for assessing the operational performance of 46 international tourist hotels (ITHs) in Taiwan over the period 1997-2002. This study is the first research that combines the discriminant power of a slack-based measure and the dynamic view of window analysis in applying DEA. It is shown that the trend of mean managerial efficiency is increasing, whereas the variation converges. Most ITHs operate at decreasing returns to scale, indicating that ITHs are facing a highly competitive environment. Taiwan's 921 earthquake in 1999, the 911 incident in 2001, and the compulsory government subsidies all play key roles which affect the ITHs' managerial performance for different operating characteristics in the short term. Results also indicate that differences in management style do have a very significant influence upon ITHs' performance over time (1997-2002). Finally, the efficiency/profitability matrix of ITHs is further examined.

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Recently Ornstein-Uhlenbeck (O-U) processes have been drawing much attention in financial engineering for modeling stochastic behavior of spot interest rates. While transition probabilities of the O-U processes are readily accessible, it is numerically cumbersome to quantify their dynamic behavior much needed in certain applications, e.g., computing the prices of barrier options and the like in financial engineering. The purpose of this paper is to develop numerical procedures for evaluating distributions of first passage times and the historical maximums of the O-U processes via the Ehrenfest process approximation. Using the fact that a sequence of Ehrenfest processes with appropriate scaling and shifting converges in law to an O-U process, it is shown that first passage times and the historical maximum of the Ehrenfest processes converge in law to those of the O-U process. Through analysis of the spectral structure of the Ehrenfest process, efficient numerical algorithms are developed, thereby providing effective approximation tools for capturing the dynamic behavior of the O-U process. The proposed numerical algorithms are systematic in that the needed computations can be done repeatedly for different values of the underlying parameters with little alterations. Some numerical results are also exhibited, demonstrating speed and accuracy of the algorithms.

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