REAL CODED VARIABLE POPULATION SIZE GENETIC ALGORITHM FOR FIXED CHARGE TRANSPORTATION PROBLEM IN MULTI-STAGE SUPPLY CHAIN NETWORK
Keywords:
Real Coded Variable Population Size Genetic Algorithm, Multi-Stage, Supply Chain Network, Fixed Charge Transportation ProblemAbstract
In this paper a mathematical model is developed for Multi-Stage Supply Chain Network (MSCN) associated with fixed charge for each route and proposed a solution procedure based on real coded variable population size Genetic Algorithm (RC-VPGA). The supply chain is often represented as a network called a supply chain network (SCN) which comprised of nodes that represent facilities (suppliers, plants, distribution centers and customers). These nodes are connected by arcs that represent the production flow. The objective of this paper is to select the optimum set of suppliers, plants, distribution centers (DCs) to be opened and the distribution network design to satisfy the customer demand with minimum total distribution cost. In many distribution problems the transportation cost consists of fixed charges, which are independent of the quantities transported, and variable costs, which are proportional to the quantities transported. The problem chosen goes beyond the traditional mathematical programming and it becomes Non- Polynomial (NP) hard while considering the fixed charges. Our new idea lies on the adoption of fixed charges for each production flow between the stages. The performance of the proposed methodology is compared with approximate and lower bound solutions. The comparison reveals that the RC-VPGA generates better solution than an approximation method and is capable of providing solution closer to the lower bound solution of the problem.
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