An Elevator Kinematics Optimisation Method for Aggregate Production Planning Based on Fuzzy MOLP Model

Pasura Aungkulanon 1, Pongchanun Luangpaiboon 2, and Roberto Montemanni 3
1. Faculty of Industrial Technology, Phranakhon Rajabhat University, Bangkok, 10220, Thailand
2. Industrial Statistics and Operational Research Unit (ISO-RU), Faculty of Engineering, Thammasat University Pathumthani, Thailand
3. Dalle Molle Institute for Artificial Intelligence (IDSIA), University of Applied Sciences of Southern Switzerland, Galleria 2, Manno 6928, Switzerland
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. 

Index Terms—aggregate production planning, fuzzy programming, elevator kinematics optimisation, harmony
search and bee algorithms

Cite: Pasura Aungkulanon, Pongchanun Luangpaiboon, and Roberto Montemanni, "An Elevator Kinematics Optimisation Method for Aggregate Production Planning Based on Fuzzy MOLP Model," International Journal of Mechanical Engineering and Robotics Research, Vol. 7, No. 4, pp. 422-427, July 2018. DOI: 10.18178/ijmerr.7.4.422-427
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