Location-inventory- redundancy allocation optimization problem in a multi-objective single- period supply chain network with stochastic demand

Allocating redundancy components is one of the most efficient and well-known ways to increase the reliability of factories; which plays an important role in responding appropriately to customer demand, timely delivery of products and cost reduction. This leads to the creation of a stable and reliable supply chain. In the present study, the subject of simultaneous optimization of facility location-inventory-redundancy allocation has been investigated. In this regard, a single-period, three-level supply chain including supplier, distributor and retailer is considered. It is assumed that demand for each retailer is stochastic and normally distributed. Also, in order to deal with the fluctuations of demand, the risk pooling strategy has been applied, as a result of which, inventory will be held only in distribution centers. For this purpose, a nonlinear integer programming model is proposed to optimize the total cost of the supply chain as well as its reliability.Due to the complexity and NP-hardness of facility location-inventory and redundancy allocation problems, a multi-objective metaheuristic algorithm based on the simulated annealing algorithm, called AMOSA, was developed to solve the foregoing problem. Finally, to validate and accredit the algorithm, its results are compared with the results of the complete enumeration of all feasible solutions.