Research on Network Optimization Problem of Automobile Service Spare Parts Supply Chain
|School||Harbin University of Science and Technology|
|Course||Computer Software and Theory|
|Keywords||supply chain management service spare parts network optimizationof supply chain np problem immune genetic algorithm|
With the high-speed development of the market economy, supply chainmanagement has been one of the most important links by which the enterpriseimproves its competitiveness. Now, supply chain management of product has beenenough mature, but the service spare parts act as the main part of after-market, itplays a more and more important role in the enterprise supply chain.Especially atpresent the product profit is not high, the product after-sales service has become thekey to increase benefits manufacturers. Network optimization is an important part ofsupply chain management, and it can make the total cost of the whole service spareparts supply chain network management to the minimum so that enterprise gains thehighest interest, by considering the inventory, logistics, construction cost and otherfactors comprehensively, and distruting service spare parts supply chain networkreasonably.Most people consider the factors incompletely for research on networkoptimization of supply chain, such as single product and single supplier model hasnot correctly reflected practical supply chain model. This paper establishes a networkoptimization model of service spare parts supply chain based on multi-products andmulti-suppliers which considers various factors such as the inventory cost, logisticscost, fixed construction cost, demand and so on. This paper strives to make the wholenetwork balanced and reasonable distribution and achieve optimization on the whole.The network optimization problem of supply chain is a typical np problem, thesolution of the model is mainly heuristic algorithm, this paper chooses the immunegenetic algorithm to solve the problem. This algorithm added the immune operatoron the basis of genetic algorithm, so it can effectively prevent the genetic algorithm"premature" phenomenon from appearing and avoid falling into local optimalsolution. Finally, the numerical examples turn out that immune genetic algorithm hasstronger self-adaptability and better optimal quality in comparison with genetic algorithm.This paper studies the network optimization problem of service spare partssupply chain in order to minimize the operating cost of supply chain network, and itprovides strategic support for enterprise decision.