A random search heuristic for a multi-objective production planning

Authors:
Mehdi Karimi-Nasab;Ioannis Konstantaras
Affiliations:
Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran;Department of Business Administration, Business Excellence Laboratory, University of Macedonia, 54006 Thessaloniki, Greece
Venue:
Computers and Industrial Engineering
Year:
2012

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Abstract

Real world production planning is involved in optimizing different objectives while considering a spectrum of parameters, decision variables, and constraints of the corresponding cases. This comes from the fact that production managers desire to utilize from an ideal production plan by considering a number of objectives over a set of technological constraints. This paper presents a new multi-objective production planning model which is proved to be NP-Complete. So a random search heuristic is proposed to explore the feasible solution space with the hope of finding the best solution in a reasonable time while extracting a set of Pareto-optimal solutions. Then each Pareto-optimal solution is considered as an alternative production plan in the hand of production manager. Both the modeling and the solution processes are carried out for a real world problem and the results are reported briefly. Also, performance of the proposed problem-specific heuristic is verified by comparing it with a multi-objective genetic algorithm on a set randomly generated test data.