Genetic algorithm for inventory positioning problem with general acyclic supply chain networks

Inventory positioning, also known as safety stock placement, in supply chain networks is an important optimisation problem that has various applications in supply chain design and configuration. In this paper, we develop a new genetic algorithm (GA) for this NP-hard problem. Our new GA features custom designed procedure to generate feasible individuals by exploiting the problem structure. It also implements a multi-start strategy to enhance solution quality. Computational results show that our GA is able to offer near optimal solutions in reasonable computational time. [Received 4 October 2014; Revised 19 October 2015; Revised 14 January 2016; Accepted 18 January 2016]

[1]  Stefan Minner,et al.  Meta-heuristics for placing strategic safety stock in multi-echelon inventory with differentiated service times , 2016, Ann. Oper. Res..

[2]  David E. Goldberg,et al.  Alleles, loci and the traveling salesman problem , 1985 .

[3]  Sartaj Sahni,et al.  Computationally Related Problems , 1974, SIAM J. Comput..

[4]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[5]  S. Orero.  A combination of the genetic algorithm and Lagrangian relaxation decomposition techniques for the generation unit commitment problem , 1997 .

[6]  In Chan Choi,et al.  A hybrid genetic algorithm for train sequencing in the Korean railway , 2009 .

[7]  Rajan Batta,et al.  On the use of genetic algorithms to solve location problems , 2002, Comput. Oper. Res..

[8]  Mitsuo Gen,et al.  A genetic algorithm approach to the bi-criteria allocation of customers to warehouses , 2003 .

[9]  Pruettha Nanakorn,et al.  An adaptive penalty function in genetic algorithms for structural design optimization , 2001 .

[10]  Sean P. Willems,et al.  Technical Note - Optimizing Strategic Safety Stock Placement in General Acyclic Networks , 2011, Oper. Res..

[11]  Charles C. Palmer,et al.  An approach to a problem in network design using genetic algorithms , 1994, Networks.

[12]  James C. Bean,et al.  A Genetic Algorithm for the Multiple-Choice Integer Program , 1997, Oper. Res..

[13]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[14]  Zhongsheng Hua,et al.  A variable-grouping based genetic algorithm for large-scale integer programming , 2006, Inf. Sci..

[15]  I. Moon,et al.  Genetic algorithms for job shop scheduling problems with alternative routings , 2008 .

[16]  Mitsuo Gen,et al.  Genetic algorithm for non-linear mixed integer programming problems and its applications , 1996 .

[17]  Sean P. Willems,et al.  Optimizing Strategic Safety Stock Placement in Supply Chains , 2000, Manuf. Serv. Oper. Manag..

[18]  Iftekhar A. Karimi,et al.  Efficient heuristics for inventory placement in acyclic networks , 2009, Comput. Oper. Res..

[19]  Haitao Li,et al.  New model and heuristics for safety stock placement in general acyclic supply chain networks , 2012, Comput. Oper. Res..

[20]  Paul R. Harper,et al.  A genetic algorithm for the project assignment problem , 2005, Comput. Oper. Res..

[21]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

[22]  David Simchi-Levi,et al.  Inventory placement in acyclic supply chain networks , 2006, Oper. Res. Lett..

[23]  Stefan Minner,et al.  Dynamic programming algorithms for multi-stage safety stock optimization , 1997 .