For the retailer on supply chain, decentralized ordering to multiple suppliers is an effective method to mitigate the risk that the retailer cannot sell the product to customers when the suppliers are down by catastrophic disasters. But decentralized ordering costs the retailer because the retailer procures products from the suppler whose procurement cost is expensive. For the retailers' cost-benefit analysis of the decentralized ordering, we address developing the risk simulator on multi-tier supply chain to evaluate the effect of risk mitigation and the cost by decentralized ordering. In order to develop the risk simulator for the multi-tier supply chain, we combine the risk simulator for the 2-tier supply chain as a building block. In addition, when the 2-tier supply chain is combined, the risk simulator calculates propagation of the risk and the cost from a 2-tier supply chain to the others. Applying the risk simulator to the real supply chain with different parameter values, the authors confirmed that the risk simulator enables to find the relationship between the cost-benefit characteristic and the multi-tier supply chain model.
This paper addresses evaluation of a decentralized procurement plan for the support of the discussion among decision-makers with considering a catastrophic disaster. For the evaluation of the decentralized procurement plan, we have formulated the decentralized procurement planning problem as 3-objective optimization problem. However, multiple-objective genetic algorithms (MOGA) to solve the problem take several minutes and display many Pareto solutions. We propose the interactive evaluation method of the decentralized procurement plan that is an expanded interactive MOGA (iMOGA) with loss evaluation simulator and solution selection by characteristics of the decentralized procurement plan. Experimental results show that the proposed method can allow the decision-makers to find their preference solutions with 38% fewer interactions than the basic iMOGA can.
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