Efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime minimisation |
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| Institution: | 1. Industrial Management, School of Engineering, University of Seville, Seville, Spain;2. Production Management, Faculty of Business Administration and Economics, University of Duisburg, Duisburg, Germany;1. College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar;2. Qatar Environment & Energy Research Institute (QEERI), Hamad Bin Khalifa University, Doha, Qatar;3. Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia;1. Department of Electronics Engineering, S. V. National Institute of Technology, Surat, Gujarat, 395007, India;2. Department of Electronics and Communication Engineering, Gandhi Institute for Technological Advancement (GITA), Bhubaneswar, India;1. Faculty of Science, Kunming University of Science and Technology, Kunming 650093, China;2. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;3. School of Management Science and Engineering, Dalian University of Technology, Dalian 116023, China;4. Department of Statistics, Feng Chia University, Taichung, Taiwan |
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| Abstract: | In this paper we analyse the performance of flowshop sequencing heuristics with respect to the objectives of makespan and flowtime minimisation. For flowtime minimisation, we propose the strategy employed by the NEH heuristic to construct partial solutions. Results show that this approach outperforms the common fast heuristics for flowtime minimisation while performing similarly or slightly worse than others which, on reward, prove to be much more CPU time-consuming. Additionally, the suggested approach is well balanced with respect to makespan and flowtime minimisation. Based on the previous results, two algorithms are proposed for the sequencing problem with multiple objectives – makespan and flowtime minimisation. These algorithms provide the decision maker with a set of heuristically efficient solutions such that he/she may choose the most suitable sequence for a given ratio between costs associated with makespan and those assigned to flowtime. Computational experience shows both algorithms to perform better than the current heuristics designed for the two-criteria problem. |
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