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A hybrid differential evolution algorithm for a stochastic location-inventory-delivery problem with joint replenishment 被引量:1
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作者 Sirui Wang Lin Wang Yingying Pi 《Data Science and Management》 2022年第3期124-136,共13页
A practical stochastic location-inventory-delivery problem with multi-item joint replenishment is studied.Unlike the conventional location-inventory model with a continuous-review(r,Q)inventory policy,the periodic-rev... A practical stochastic location-inventory-delivery problem with multi-item joint replenishment is studied.Unlike the conventional location-inventory model with a continuous-review(r,Q)inventory policy,the periodic-review inventory policy is adopted with multi-item joint replenishment under stochastic demand,and the coordinated delivery cost is considered.The proposed model considers the integrated optimization of strategic,tactical,and operational decisions by simultaneously determining(a)the number and location of distribution centers(DCs)to be opened,(b)the assignment of retailers to DCs,(c)the frequency and cycle interval of replenishment and delivery,and(d)the safety stock level for each item.An intelligent algorithm based on particle swarm optimization(PSO)and adaptive differential evolution(ADE)is proposed to address this complex problem.Numerical experiments verified the effectiveness of the proposed two-stage PSO-ADE algorithm.A sensitivity analysis is presented to reveal interesting insights that can guide managers in making reasonable decisions. 展开更多
关键词 location-inventory problem Joint replenishment Stochastic demand Particle swarm optimization Differential evolution
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Research on Location-Inventory Model in Grain Emergency Network
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作者 Lin Wang Wenzhuo Liang Yunxian Hou 《Journal of Computer and Communications》 2014年第14期52-58,共7页
Once the disaster occurred, a huge amount of grain supply is needed from disaster area. Because of the short shelf life, grain is very strict with reserve environment and needed to rotate on a regular basis in the pro... Once the disaster occurred, a huge amount of grain supply is needed from disaster area. Because of the short shelf life, grain is very strict with reserve environment and needed to rotate on a regular basis in the process of reserves. Considering the limitations of existing related research, this paper presented a facility location model for grain emergency network that incorporates inventory factors and rotation mechanism, and then designed genetic algorithm based on Matlab to solve the model. Finally we verified the feasibility and effectiveness of the algorithm by computational examples and presented the directions for future work. 展开更多
关键词 location-inventory GRAIN EMERGENCY NETWORK GENETIC Algorithm
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Research on a Distribution Center Location Model Based on a Particle Swarm Optimization Algorithm 被引量:2
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作者 WANG Fei 1,2,HU Xin-bu3,JIA Tao41 School of Economy and Management,Chang’an University,Xi’an 710064,P.R.China 2 Institute of Human Geography,Xi’an International Studies University,Xi’an 710061,P.R.China +1 位作者 3 Architecture Engineering Department,Engineering College of Armed Police Forces,Xi’an 710086,P.R.China 4 School of Management,Xi’an Jiaotong University,Xi’an 710069,P.R.China 《International Journal of Plant Engineering and Management》 2009年第3期151-157,共7页
Logistics is supposed to be the important source of profits for the enterprises besides reducing material consumption and improving labor productivity. Transportation costs, distribution center construction costs, ord... Logistics is supposed to be the important source of profits for the enterprises besides reducing material consumption and improving labor productivity. Transportation costs, distribution center construction costs, ordering costs, safe inventory costs and inventory holding costs are the important parts of the total logistics costs. In this paper, based on the research results of LMRP( location model of risk pooling) location with fixed construction cost, the LMRPVCC ( location model of risk pooling based on variable construction cost) will be introduced. Applying particle swarm optimization to several computational instances, the authors find the suboptimum solution of the model. 展开更多
关键词 location-inventory particle swarm optimization algorithm variable cost of construction
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