| With increasing market competition and consumer demand is becoming more diverse and personalized,enterprises are faced with how to cost large-scale manufacturing to meet the diverse needs of consumers.To balance the lead time,production costs and consumers’ diverse demand,more and more enterprises to adopt ATO(assemble-to-order,ATO)production mode.In ATO production mode,product family ATO manufacturers can provide customized products to consumers,but only assemble limited parts into a limited product type,so it is necessary to study on how to use a limited product type to meet the infinite diversity and personalized needs.Meanwhile,the traditional components replenishment policy has been unable to apply to ATO production mode,it is necessary to study components replenishment strategy of the ATO system as well.This paper uses storage theory,game theory,mass customization theory,the theory of consumer behavior and intelligent algorithm theory,to establish theoretical model of the above key issues on the production and recovery of ATO system,which are ATO manufacturer’s product selection and pricing strategy based on multi-market and consumer heterogeneity,components replenishment policy of ATO supply chain when EOQ and JIT modes coexist.And come out the optimal production management strategy of ATO system,which can provide a theoretical basis to the formulation of these policies for the manufacturing companies.Firstly,this paper considers consumers can be subdivided into a number of different markets,consumers in each market have different preferences and price sensitivity to various products of a same product family,proposes an ATO manufacturer’s product selection and pricing model to study their product selection and pricing strategies,including product selection,pricing and sales peroid length of products,and the replenish quantity of all the components,and then proposes a genetic simulated annealing algorithm to obtain the optimal solution.Secondly,this paper considers the consumer heterogeneity and market segmentation,as well as the decreasing consumers’ utility of the same product family of products with time increasing,proposes an ATO products selection and pricing model under time-varying utility,to study the selection and pricing strategy of ATO manufacturers.Meanwhile,an genetic simulation annealing algorithm is proposed to obtain the optimal solution of the model.Finally,this paper considers ATO manufacturers using EOQ and JIT replenish mode for components replenishment at the same time,to build a production and replenishment model of ATO supply chain to study the components replenishment policy of ATO manufacturer and production management strategy of suppliers.Meanwhile,combining with quantum computing,genetic algorithm and simulated annealing algorithm,this paper proposes a quantum genetic simulated annealing algorithm to obtain the optimal solution,and verifys the validity and robustness of the algorithm,and finds the optimal components replenishment policies of ATO supply chain.This article has the following innovations:(1)Different from the existing studies about product line design and product pricing strategy based on consumer behavior,this paper considers consumers to be divided into several segments,consumers in each market heterogeneity,and they make purchasing decisions according to according to utilities of products in a same product family,to study the product selection and pricing strategy of the ATO manufacturers when they provide limited products of a product family to meet different needs of consumers in various market segments.(2)In considering the consumer market segmentation and consumer heterogeneity,we also consider the decreasing consumers’ utility of the same product family of products with time increasing,to study the product selection and pricing strategy of the ATO Manufacturer.(3)Different from the existing studies on ATO supply chain which using only a single replenishment mode to replenish components,this paper considers ATO manufacturers simultaneously use JIT and EOQ to replenishment components from suppliers,to study the optimal components replenishment strategy of ATO system.And the improved quantum genetic simulated annealing algorithm is used to solve the optimal strategy. |
