A tabu search algorithm for solving economic lot scheduling problem
An electronic copy of the full paper will be provided upon request by e-mail: [email protected] J Heuristics (2006) 12:413–426 DOI 10.1007/s10732-006-6017-7
A tabu search algorithm for solving economic lot scheduling problem S. A. Raza · A. Akgunduz · M. Y. Chen
Submitted in April 2005 and accepted by Rafael Mart´ı in November 2005 after 1 revision C Springer Science + Business Media, LLC 2006
Abstract The economic lot scheduling problem has driven considerable amount of research. The problem is NP-hard and recent research is focused on finding heuristic solutions rather than searching for optimal solutions. This paper introduces a heuristic method using a tabu search algorithm to solve the economic lot scheduling problem. Diversification and intensification schemes are employed to improve the efficiency of the proposed Tabu search algorithm. Experimental design is conducted to determine the best operating parameters for the Tabu search. Results show that the tabu search algorithm proposed in this paper outperforms two well known benchmark algorithms. Keywords Economic lot scheduling problem . Tabu search . Neighborhood search and design of experiment
1 Introduction The Economic Lot Scheduling Problem (ELSP) deals with the production assignment of several products sharing the same production facility. The objective of the ELSP is to minimize total production cost. It is a constrained optimization problem in which production scheduling is done in such a way that all products are manufactured and their demands satisfied during the planning period. The production scheduling decision includes the determination of the production sequence and cycle time of each product in the sequence. A variety of methods have been proposed to solve the ELSP. In general, these methodologies can be categorized S. A. Raza · A. Akgunduz () · M. Y. Chen Department of Mechanical and Industrial Engineering, Concordia University, H549, 1455 de Maisonneuve Blvd. W. Montreal, Quebec H3G 1M8, Canada e-mail: [email protected] S. A. Raza e-mail: asif [email protected] M. Y. Chen e-mil: [email protected] Springer
A tabu search algorithm for solving economic lot scheduling problem S. A. Raza · A. Akgunduz · M. Y. Chen
Submitted in April 2005 and accepted by Rafael Mart´ı in November 2005 after 1 revision C Springer Science + Business Media, LLC 2006
Abstract The economic lot scheduling problem has driven considerable amount of research. The problem is NP-hard and recent research is focused on finding heuristic solutions rather than searching for optimal solutions. This paper introduces a heuristic method using a tabu search algorithm to solve the economic lot scheduling problem. Diversification and intensification schemes are employed to improve the efficiency of the proposed Tabu search algorithm. Experimental design is conducted to determine the best operating parameters for the Tabu search. Results show that the tabu search algorithm proposed in this paper outperforms two well known benchmark algorithms. Keywords Economic lot scheduling problem . Tabu search . Neighborhood search and design of experiment
1 Introduction The Economic Lot Scheduling Problem (ELSP) deals with the production assignment of several products sharing the same production facility. The objective of the ELSP is to minimize total production cost. It is a constrained optimization problem in which production scheduling is done in such a way that all products are manufactured and their demands satisfied during the planning period. The production scheduling decision includes the determination of the production sequence and cycle time of each product in the sequence. A variety of methods have been proposed to solve the ELSP. In general, these methodologies can be categorized S. A. Raza · A. Akgunduz () · M. Y. Chen Department of Mechanical and Industrial Engineering, Concordia University, H549, 1455 de Maisonneuve Blvd. W. Montreal, Quebec H3G 1M8, Canada e-mail: [email protected] S. A. Raza e-mail: asif [email protected] M. Y. Chen e-mil: [email protected] Springer
