A hybrid heuristic algorithm for the multistage supply chain network problem

In recent years, many developments in logistics were connected to the need for information in an efficient supply chain flow. The supply chain is often represented as a network called a supply chain network (SCN) that is comprised of nodes that represent facilities (suppliers, plants, distribution centers and customers). Arcs connect these nodes along with the production flow. A multistage SCN (MSCN) is a sequence of multiple SCN stages. The flow can only be transferred between two consecutive stages. The MSCN problem involves the choice of facilities (plants and distribution centers) to be opened and the distribution network design must satisfy the demand with minimum cost. In this paper, a revised mathematical model is first proposed to correct the fatal error appearing in the existing models. An efficient hybrid heuristic algorithm (HHA) was developed by combining a greedy method (GM), the linear programming technique (LP) and three local search methods (LSMs) (always used in solving the scheduling problem). The pair-wise exchange procedure (XP), the insert procedure (IP) and the remove procedure (RP) to solve the MSCN problem. Preliminary computational experiments demonstrate the efficiency and performance of the proposed HHA.

[1]  George B. Dantzig,et al.  Linear programming and extensions , 1965 .

[2]  C. Poirier,et al.  Advanced Supply Chain Management: How to Build a Sustained Competitive Advantage , 1999 .

[3]  M. Gen,et al.  Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach , 2002 .

[4]  Pierre Hansen,et al.  A Plant and Warehouse Location Problem , 1977 .

[5]  Hartmut Stadtler,et al.  Supply Chain Management and Advanced Planning , 2000 .

[6]  M. Todd,et al.  The Ellipsoid Method: A Survey , 1980 .

[7]  Wei-Chang Yeh.  A new branch-and-bound approach for the n/2/flowshop/alphaF+betaCmax flowshop scheduling problem , 1999, Comput. Oper. Res..

[8]  M. Rönnqvist,et al.  Lagrangian heuristics for the two-echelon, single-source, capacitated facility location problem , 1997 .

[9]  Michael J. Todd,et al.  Feature Article - The Ellipsoid Method: A Survey , 1981, Oper. Res..

[10]  Hanif D. Sherali,et al.  Linear Programming and Network Flows , 1977 .

[11]  Américo Azevedo,et al.  Order planning for networked make-to-order enterprises—a case study , 2000, J. Oper. Res. Soc..

[12]  W. Yeh.  An efficient branch-and-bound algorithm for the two-machine bicriteria flowshop scheduling problem , 2001 .

[13]  Choong Y. Lee,et al.  A cross decomposition algorithm for a multiproduct-multitype facility location problem , 1993, Comput. Oper. Res..

[14]  Andreas T. Ernst,et al.  Comparison of Algorithms for the Degree Constrained Minimum Spanning Tree , 2001, J. Heuristics.

[15]  G. Raidl,et al.  Prüfer numbers: a poor representation of spanning trees for evolutionary search , 2001 .

[16]  Guisseppi A. Forgionne,et al.  Corporate Management Science Activities: An Update , 1983 .

[17]  Narendra Karmarkar,et al.  A new polynomial-time algorithm for linear programming , 1984, Comb..