Cost reduction in logistics has been an important issue in supply chain management. Cross-docking is known as one of distribution strategies to cope with cost reduction. A cross-docking center is a warehouse in which incoming commodities from venders are transshipped and from which stores are supplied, without holding any stock in it. In this paper, we consider a cross-docking network design problem and propose a mathematical programming model for it. In this problem, decision variables are whether each cross-docking center is established or not, transportation quantity among venders, cross-docking points and stores in the established network. Transportation is performed by vehicles and we consider two types of vehicles. The difference between them is their capacity. This problem can be formulated into a mixed integer programming problem. We reformulate it into a set-partitioning-type problem and apply the column generation method. In the formulation, each column includes information corresponding to a “transportation pattern” giving the type and the number of vehicles used as well as their origin and destination. We also propose an acceleration strategy of column generation for finding, with a simple detection method, “effective” sub-problems which tend to yield columns with negative reduced cost. Finally, we demonstrate numerical results from computational experiments. The results suggest that our approach works well and provides good solutions within acceptable time.

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The standard particle swarm optimization (PSO) is an evolutionary algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. Many numerical experiments have reported that PSO can provide high-quality solutions. However, PSO cannot yield good solutions for large-scale problems; that is, high-dimensional problems. For this problem, this paper proposes new algorithms using the idea of effective particles moving. The basic idea is that moving of particles is updated according to the Cauchy distribution. The Cauchy distribution has a Gaussian-like peak and Lorentzian wing that imply occasional long jumps among local sampling. This proper trade-off between local search and semi-global search allows effective moving of particles. Moreover, this algorithm has been improved using the new search procedure that assumes a particle swarm is frequently reconstructed by the idea of scatter search. This search procedure operates on a set of good particles, the reference set, by combining these particles to create new ones. It uses strategies for search diversification and intensification by introducing the Cauchy distribution for the process of combining particles. The goal of this methodology is to enable the implementation of solution procedures that can derive new better particle swarms from combined elements. Finally, comparing the results on a set of benchmark multimodal functions, the proposed algorithm shows competitive performance with improved convergence speed and high optimizing precision for difficult problems.

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The quality of lots has been conservatively evaluated based on attribute properties such as the proportion or number of non-conforming items in the lot. On the other hand, Taguchi proposed a concept of quality loss as a measure to evaluate the quality of items based on variable properties instead of attribute properties. Incidentally, Robert proposed the attribute repetitive group sampling plan on operating characteristics instead of the attribute single sampling plan on operating characteristics. In this way, the attribute repetitive group sampling plan can be understood as a more efficient sampling plan from the viewpoint of comparison of the required number of samples, since the required number of samples in this plan is less on average than that of the traditional attribute single sampling plans. In this article, for the purpose of improving the efficiency of the variable sampling plan based on quality loss proposed by Arizono et al., the variable repetitive group sampling plan is considered. Specifically, we show the design procedure for finding out inspection criterions and sample size under the desired operating characteristics indexed by quality loss. By illustrating that average sample number in the inspection is reduced, the effectiveness of the proposed sampling plans is verified.

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This report examines results of pupil reaction received by stimuli of occupation-related words. The relationship between subjective vocational preference and the size of pupils is considered. In the case that examinees see occupation-related words which they answered positively to in a paper-based questionnaire test, the size of examinees' pupils expands significantly. In contrast, in the case that they see words which they answered negatively to in the same paper-based questionnaire test, the size of examinees' pupils does not change.
We also consider how affectation influences pupil size. Under the condition that examinees are ordered to give misleading responses, in the questionnaire test, they come up with different answers from their original vocational preference. However, in the pupil test, there is no effect due to this affectation. We confirm that the size of pupils was not influenced by temporary environments and intentional motivation, as true vocational preference reflects.
Based on these results, we conclude that the pupil size index has potential for use in the process of screening new graduates to measure vocational preference, resolving problems that traditional questionnaire tests have faced.

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In this paper we develop theories of product architecture formation. Conventionally, when a new technology is implemented in a product with modular architecture, the modular architecture is transformed into integral architecture. However, since there is little research for product architecture formation of automobile engine components, we discuss whether existing theories of product architecture explain complex products such as automobile engines. At first glance, existing theories are not adaptable to engine components, but they are adaptable when concept hierarchy is considered. It is difficult to understand the appropriate product architecture. This study supports the importance of the concept of hierarchy in product architecture.

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Electric vehicles are regarded as eco-friendly automobiles. However, there are several obstacles preventing their widespread use. One of the most important and difficult issues is the rechargeable battery. To analyze this problem, we model the facility location problem of a quick electric recharging station for electric vehicles based on the combinatorial optimization problem and derive the optimal location solution using mean field approximation developed in statistical physics. Moreover, our proposed algorithm is validated using numerical experiments.

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