TY - JOUR

T1 - Combining genetic approach and integer programming to solve multi-facility economic lot-scheduling problem

AU - Chan, Hing Kai

AU - Chung, Sai Ho

AU - Chan, Tak Ming

N1 - Funding Information:
Acknowledgments An earlier version of this paper concerning single facility problem has been presented in DET2009 conference held at the University of Hong Kong during 14–16 December 2009 and included in the conference proceeding published by Springer. The authors are also grateful to the Research Office of The Hong Kong Polytechnic University for supporting this project, which is supported under the grant number A-PD0N. The authors would also like to thank the anon- ymous reviewers who provide the authors with insightful and constructive comments, which have helped improve the quality of this paper.

PY - 2012/12

Y1 - 2012/12

N2 - Economic lot-scheduling problem (ELSP) has been studied since the 1950's. ELSP deals with the scheduling of the production of several items on a single facility in a cyclical pattern. The facility can only produce one single item at a time, and there is a set-up cost and set-up time associated with each item. Because of the rapid development of many emerging markets nowadays, many common items are produced in different places in order to satisfy the demands in different markets. This becomes the multi-facilities ELSP problems. In ELSP problems, it is known that if more items types to be produced by the facility, the production frequency of each item type will increase because of the balancing of the production rate and the demand rate. Consequently, the number of set-up time and set-up cost increases accordingly. Thus, reallocating the common items, which can be produced in any facilities, to be produced only on certain facility can certainly reduce the number of production frequency, and lead to lower related costs. The objective of this paper is to propose an optimization methodology combining Integer Programming and Genetic Algorithm to solve multi-facility ELSP problems. This paper proposes to divide themain problem into amaster problem and sub-problems, which are solved by Integer Programming and Genetic Algorithm respectively. To demonstrate the significance of reallocating the common items and aggregating them to produce in certain facility, several models have been designed and tested. The comparison of the models demonstrates the reduction of the costs benefited by result of common items reallocation.

AB - Economic lot-scheduling problem (ELSP) has been studied since the 1950's. ELSP deals with the scheduling of the production of several items on a single facility in a cyclical pattern. The facility can only produce one single item at a time, and there is a set-up cost and set-up time associated with each item. Because of the rapid development of many emerging markets nowadays, many common items are produced in different places in order to satisfy the demands in different markets. This becomes the multi-facilities ELSP problems. In ELSP problems, it is known that if more items types to be produced by the facility, the production frequency of each item type will increase because of the balancing of the production rate and the demand rate. Consequently, the number of set-up time and set-up cost increases accordingly. Thus, reallocating the common items, which can be produced in any facilities, to be produced only on certain facility can certainly reduce the number of production frequency, and lead to lower related costs. The objective of this paper is to propose an optimization methodology combining Integer Programming and Genetic Algorithm to solve multi-facility ELSP problems. This paper proposes to divide themain problem into amaster problem and sub-problems, which are solved by Integer Programming and Genetic Algorithm respectively. To demonstrate the significance of reallocating the common items and aggregating them to produce in certain facility, several models have been designed and tested. The comparison of the models demonstrates the reduction of the costs benefited by result of common items reallocation.

KW - Economic lot-scheduling problem

KW - Genetic Algorithm

KW - Integer programming

KW - Multi-facility

UR - http://www.scopus.com/inward/record.url?scp=84870930108&partnerID=8YFLogxK

U2 - 10.1007/s10845-010-0474-4

DO - 10.1007/s10845-010-0474-4

M3 - Article

AN - SCOPUS:84870930108

SN - 0956-5515

VL - 23

SP - 2397

EP - 2405

JO - Journal of Intelligent Manufacturing

JF - Journal of Intelligent Manufacturing

IS - 6

ER -