Order acceptance and scheduling to maximize total net revenue in permutation flowshops with weighted tardiness

• This paper studies the permutation flowshop scheduling problem with order acceptance and weighted tardiness.
• The proposed algorithm provides a practical means of solving this problem.
• Experimental results reveal that the proposed algorithm outperforms the state-of-the-art algorithm.

The order acceptance and scheduling (OAS) problem is important in make-to-order production systems in which production capacity is limited and order delivery requirements are applied. This study proposes a multi-initiator simulated annealing (MSA) algorithm to maximize the total net revenue for the permutation flowshop scheduling problem with order acceptance and weighted tardiness. To evaluate the performance of the proposed MSA algorithm, computational experiments are performed and compared for a benchmark problem set of test instances with up to 500 orders. Experimental results reveal that the proposed heuristic outperforms the state-of-the-art algorithm and obtains the best solutions in 140 out of 160 benchmark instances.

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