A Study On The Vertical Extended Models Using Joint Replenishment Policy Based On Fruit Fly Optimization Algorithm

Joint replenishment(JR)policy can achieve total cost saving through the sharing of the main ordering cost and by grouping and purchasing multiple items.In order to control the total cost effectively under global purchase background,the application of joint replenishment policy becomes more and more popular.In addition,it is of great practical significance to integrate and optimize the procurement,location,and distribution under the environment of supply chain management.Therefore,the design of practical optimization models based on the above strategies and easy implementation algorithm with high performance has great theoretical significance and high application value.Considering the requirements of precise management of order quantity allocation,distribution and location,three extended joint replenishment models are proposed by overcoming the limitations of traditional methods.In order to solve these NP-hard problems effectively,the improved fruit fly optimization algorithm(FOA)is designed with high accuracy,versatility and good stability by integrating the advantages of other evolutionary technologies.Typical standard function test are carried out to verify the good comprehensive performance of the proposed algorithm,and it provides a methodllogical support for solving the above optimization models.The main work includes the following four aspects:Firsly,a hybrid FOA(HFOA)using improved location information exchange mechanism is proposed.The basic FOA is faced with the challenges of poor diversity of the swarm and weak local search ability because of the improper osphresis operation and vision operation.To overcome these limitations synthetically,it is necessary to improve the swarm diversity in a more efficient way and well balance the global search and local search abilities.The proposed HFOA enables flies to communicate with each other and conduct local search in a swarm based approach.Moreover,osphresis operation is conducted in probability to balance the global search and local search processes.A mutation strategy called cataclysm policy is designed to help the flies jump out of the local extreme points.Eighteen complex continuous benchmark functions are used to test the performance of HFOA.Numerical experiments results indicate that HFOA outperforms main state-of-the-art algorithms.Secondly,the coordinated order quantity allocation problems based on joint replenishment policy are studied and algorithms are provided.The basic model considering suppliers selection and the improved HFOA is proposed to solve this problem.Moreover,a new coordinated order quantity allocation model considering grouping constraint caused by the heterogeneity of items is developed.Results of contrastive numeric examples show that the HFOA outperforms simulated annealing algorithm(SA)and standard FOA in solving this problem and its extension type.The effectiveness of HFOA is further verified by randomly generated large-scale problems.Thirdly,the practical joint replenishment and delivery(JRD)models are studied by considering resources constraints.The classic JRDs with and without resources constraints are used to vefrify the performcance of HFOA,and results show HFOA is better than an improved FOA,differential evolution algorithm(DE)and GA.Then,the cost caused by trade credit is examphsized and a new and practical JRD model by considering trade credit and transportation resource constraint is proposed.Results of randomly generated JRDs indicate that HFOA can always obtain slightly lower total costs than DE and GA under different situations.The comprehensive performance of HFOA is satisfactory for practicability requirements for solving complex optimization problems.Lastly,a new joint replenishment-location-delivery model is studied considering resource constraints.The proposed model with transport capacity constraint,which permits shortage,is more practical.An effective algorithm based on HFOA is designed to solve the proposed model.Compared with other popular algorithms,numerical studies show the effectiveness of the proposed HFOA.Finally,the sensitivity analysis is further conducted to discuss the influence of parameters on the total cost,which can provide useful references for operations managers to make better decisions.