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We study an inventory routing problem (IRP) for the restaurant chain. We proposed a model a multi-product multi-vehicle IRP (MMIRP) with multi-compatibility and site-dependency (MMIRP-MCSD). The problem was formulated as a mixed integer programming (MIP). This model is difficult to solve because it is a problem that integrates MMIRP, a multi-compartment vehicle routing problem (MCVRP), and a site dependent VRP (SDVRP), each of which is difficult even by itself. Therefore, in this study, we proposed three-stage Math Heuristics based on the cluster-first and route-second method. In the numerical experiment, verification was performed using actual data, and knowledge on the decision making of the optimum vehicle type was obtained.

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.

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