Common due-date determination and sequencing using tabu search

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Abstract

Tabu Search techniques are adapted to a single-machine scheduling problem where a common due-date for a set of jobs is determined. The problem is to determine an optimal sequence σ and the associated optimal due-date d which minimize the sum of weighted earliness and tardiness values. This paper presents a Tabu Search based approach which is more efficient for solving larger problems than any existing solution method.

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  • Cited by (14)

    • A survey of the state-of-the-art of common due date assignment and scheduling research

      2002, European Journal of Operational Research
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      James (1997) proposes to use tabu search for both restricted and unrestricted TWET problems. Hao et al. (1996) consider the common due date determination and sequencing using tabu search for the TWET problem with symmetric weights; for asymmetric weights, Lee and Kim (1995) propose a genetic algorithm. Note that James (1997) and Lee and Kim (1995) restrict their search to sequences starting at time zero, and it can lead to excluding optimal schedules from the search process.

    • A Particle Swarm Optimization Algorithm for Scheduling Against Restrictive Common Due Dates

      2013, International Journal of Computational Intelligence Systems
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    †‡

    Qi Hao is an Associate Professor in the Division of System Engineering, Department of Automatic Control at North-eastern University of China. She received her M.Sc. and Ph.D. degrees in system engineering from Northeastern University. She has published articles in Computers and Industrial Engineering and some international conference proceedings. Her research interests include production and inventory control, production scheduling and combinatorial optimization.

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    Zihou Yang is a Professor of System Engineering and Automatic Control at Northeastern University of China. He received his B.Sc. and M.Sc. degrees from Wuhan University. He has published articles in Decision Sciences, Large Scale System and International Journal of Control. His research interests include production and inventory management, computer simulation and application of AI.

    Dingwei Wang is a Professor of System Engineering at Northeastern University of China. He received his M.Sc. and Ph.D. degrees from Northeastern University. He has published articles in International Journal of Production Research, Computers and Industrial Engineering and many international conference proceedings. His research interests are in production and inventory management, combinatorial optimization, and simulation and modelling.

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    Zheng Li is a doctoral student in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He obtained iis B.Sc. and M.Sc. from Tsinghua University and Chinese Scientific and Technological University, China. His research interests include computer simulation and AI technique.

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