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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 1679315, 9 pages
Research Article

Enhanced Simulated Annealing for Solving Aggregate Production Planning

1Department of Mathematics, Faculty of Science, Universiti Putra Malaysia, Malaysia
2Department of Statistics, Faculty of Administration and Economics, University of Baghdad, Baghdad, Iraq
3Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Putra Malaysia, Malaysia

Received 28 March 2016; Accepted 11 July 2016

Academic Editor: Sergii V. Kavun

Copyright © 2016 Mohd Rizam Abu Bakar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Simulated annealing () has been an effective means that can address difficulties related to optimisation problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning () is one of the most considerable problems in production planning, in this paper, we present multiobjective linear programming model for APP and optimised by . During the course of optimising for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state will generate only one in next state that will make the search slower and the drawback is that the search may fall in local minimum which represents the best solution in only part of the solution space. In order to enhance its performance and alleviate the deficiencies in the problem solving, a modified () is proposed. We attempt to augment the search space by starting with solutions, instead of one solution. To analyse and investigate the operations of the MSA with the standard and harmony search (), the real performance of an industrial company and simulation are made for evaluation. The results show that, compared to and , offers better quality solutions with regard to convergence and accuracy.