Shunichi Ohmori

Bio: Shunichi Ohmori is an academic researcher from Waseda University. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 5, co-authored 31 publications receiving 73 citations.

Solving Facility Layout Problem via Particle Swarm Optimization

Abstract: This paper targets the Facility Layout Problem (FLP), which has many practical applications and known to be NP-hard. During recent decades, a number of algorithms have been proposed to solve this problem. Most of those algorithms try to solve this problem by encoding layout candidates and using combinational optimization techniques to obtain the best one among those encoded candidates. However, since there exist layouts which cannot be represented by those encoding techniques, there is possibility of missing the searching opportunity for the optimal solution. To overcome this problem, this paper is concerned with the development of algorithm to solve FLP by searching continuously optimal coordinate of each department. In particular, this paper proposes an algorithm solving FLP via Particle Swarm Optimization (PSO), which is known to be effective for many types of continuous optimization problem.

A Framework of Managing Supply Chain Disruption Risks Using Network Reliability

Abstract: This paper discusses how to manage supply chain disruption risks from natural disasters or other low-likelihood-highimpact risk drivers. After the catastrophic earthquake in Eastern Japan and the severe flood in Thailand, most companies have been attempting to re-establish the business continuity plan to prevent their supply chain from disruption. However, the challenges for managers and individual risks are often interrelated, and thus, actions that mitigate one risk can end up being no contribution as a whole. In this paper, we describe a framework for assessing how much impact individual mitigation strategies have on the entire supply chain protection against disruption, using network reliability. We propose three categories of risk-mitigation approaches: Stabilization, Absorption, and Duplication. We analyze the situation under which each of these strategies is the best suitable. With a clear understanding of relations between these mitigation strategies and the entire supply chain risks, managers can select effective risk-reduction approaches to their supply chain.

Application of AHP/DEA to Facility Layout Selection

Abstract: Facility location selection is a multi-criteria decision problem and has a strategic importance for many companies, so it is very important to select alternative locations using appropriate methods. The aim of this study is to use analytic hierarchy process (AHP) and pure output data envelopment analysis (DEA) methods for facility location selection. After determining the factors that affect the facility location decisions, pure output DEA is used to construct the comparison matrix, then AHP is applied to calculate the weights of the alternative locations. In this method the known data is fully used and the influence of personal factors is avoided. Finally an example is illustrated to prove the method effective.

Management Models and Industrial Applications of Linear Programming

Abstract: (1962). Management Models and Industrial Applications of Linear Programming. Journal of the Operational Research Society: Vol. 13, No. 3, pp. 274-275.

Fuzzy Multiple Attribute Decision Making Methods And Applications

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Integrating Closed-loop Supply Chains and Spare Parts Management at IBM

Abstract: textEver more companies are recognizing the benefits of closed-loop supply chains that integrate product returns into business operations. IBM has been among the pioneers seeking to unlock the value dormant in these resources. We report on a project exploiting product returns as a source of spare parts. Key decisions include the choice of recovery opportunities to use, the channel design, and the coordination of alternative supply sources. We developed an analytic inventory control model and a simulation model to address these issues. Our results show that procurement cost savings largely outweigh reverse logistics costs and that information management is key to an efficient solution. Our recommendations provide a basis for significantly expanding the usage of the novel parts supply source, which allows for cutting procurement costs.