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Integrating two-agent scheduling and order acceptance problems to maximise total revenue by bounding each agent penalty function

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  • Mohammad Reisi-Nafchi
  • Ghasem Moslehi

Abstract

This paper integrates the two-agent scheduling problem and the order acceptance and scheduling problem, to form a single problem for further investigation. The idea originates from real life situations in which manufacturers deal with different customers, each having different requests. It is, therefore, assumed in the new problem that two customer (agent) types exist while each has their specific penalty functions. The penalty function of the first agent is the total lateness while that of the second is the number of tardy orders. The objective is maximising the total revenue of accepted orders by bounding each agent's penalty function. For this problem, a pseudo-polynomial dynamic programming algorithm is developed. It was shown that the algorithm is capable of optimally solving all the problem instances up to 50 orders in size. The algorithm is found to be capable of solving 87.15% of the instances with 90 orders.

Suggested Citation

  • Mohammad Reisi-Nafchi & Ghasem Moslehi, 2015. "Integrating two-agent scheduling and order acceptance problems to maximise total revenue by bounding each agent penalty function," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 20(3), pages 358-384.
    • Handle: RePEc:ids:ijsoma:v:20:y:2015:i:3:p:358-384
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    Cited by:

    1. Joonyup Eun & Chang Sup Sung & Eun-Seok Kim, 2017. "Maximizing total job value on a single machine with job selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 998-1005, September.

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