An allocation and distribution model for perishable products
Operations Research
Computers and Operations Research
Material management in decentralized supply chains
Operations Research
An inventory model embedded in designing a supply contract
Management Science
Improved heuristic methods for multiple stage production planning
Computers and Operations Research
Probabilistic Analyses and Algorithms for Three-Level Distribution Systems
Management Science
A Method for the Solution of the Nth Best Path Problem
Journal of the ACM (JACM)
Production-distribution planning in supply chain considering capacity constraints
Computers and Industrial Engineering - Supply chain management
Computers and Industrial Engineering - Supply chain management
Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach
Computers and Industrial Engineering - Supply chain management
An evolutionary algorithm for optimizing material flow in supply chains
Computers and Industrial Engineering
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
Genetic subgradient method for solving location-allocation problems
Applied Soft Computing
An exact algorithm for multi depot and multi period vehicle scheduling problem
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Heuristics for a multiperiod inventory routing problem with production decisions
Computers and Industrial Engineering
Multi-criteria mathematical model for designing the distribution network of a consumer goods company
Computers and Industrial Engineering
Study on product quality tracing technology in supply chain
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
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In this paper, the distribution planning model for the multi-level supply chain network is studied. Products which are manufactured at factory are delivered to customers through warehouses and distribution centers for the given customer demands. The objective function of suggested model is to minimize logistic costs such as replenishment cost, inventory holding cost and transportation cost. A mixed integer programming formulation and heuristics for practical use are suggested. Heuristics are composed of two steps: decomposition and post improving process. In the decomposition heuristics, the problems are solved optimally only considering the transportation route first by the minimum cost flow problem, and the replenishment plan is generated by applying the cost-saving heuristic which was originally suggested in the manufacturing assembly line operation, and integrating with the transportation plan. Another heuristic, in which the original model is segmented due to the time periods, and run on a rolling horizon based method, is suggested. With the post-improving process using tabu search method, the performances are evaluated, and it was shown that solutions can be computed within a reasonable computation time by the gap of about 10% in average from the lower bound of the optimal solutions.