Hybrid improved cuckoo search algorithm and genetic algorithm for solving Markov-modulated demand

摘要: One of the fundamental problems in supply chain management is to design effective inventory control policies for models with stochastic demands because efficient can both maintain a high customers’ service level and reduce unnecessary over under-stock expenses which are significant key factors profit or loss an organization. In this study, new formulation system analyzed under discrete Markov-modulated demand. We employ simulation-based optimization that combines simulated annealing pattern search ranking selection (SAPS&RS) methods approximate near-optimal solutions problem. After determining values demand, we novel approach achieve minimum cost total SCM (Supply Chain Management) network. our proposed approach, hybrid improved cuckoo algorithm (ICS) genetic (GA) presented as main platform solve The computational results demonstrate effectiveness applicability approach.