Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—This study proposes a multi-objective linear programming model for solving the multi-product aggregate production planning (APP) decision problem for Topline Co., Ltd. in Thailand. The model attempts to minimise total production and work force costs and carrying inventory costs to bring a planning framework for the industrial resources management under complex information environment. The proposed model yields an efficient compromise solution and the overall levels of decision making satisfaction with the multiple objectives via the fuzzy programming using the elevator kinematics optimisation (EKO) algorithm including its hybridisations of harmony search and bee algorithms. The comparisons are made for two different levels of inventory. It can be concluded that the EKO is slightly more effective than the other hybrid approaches in terms of quality of solutions. However, there is no difference in required computation time. The basic idea is to produce reliable solution in search space with the random external command in escaping from local trap during searching for a better solution. Numerical results demonstrate the robustness and effectiveness of the developed EKO method.
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