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Scheduling Identical Jobs on Uniform Parallel Machines Under Position-Based Learning Effects

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Abstract

This research considers the problem of scheduling identical jobs on uniform parallel machines for the individual minimization of several different performance measures under position-based learning effects. The performance measures include total weighted completion time, total tardiness, total weighted tardiness, and maximum lateness. We formulate these problems as assignment problems with nonlinear or linear objectives. The n earliest completion times can be used in non-decreasing order to reduce the number of variables significantly and to find optimal solutions efficiently. Our computational results show that it is more efficient to formulate these problems as assignment problems with nonlinear objectives and a few variables and constraints than it is to formulate them as linear programming models with many variables and constraints.

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Authors and Affiliations

  1. Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan

    Yang-Kuei Lin

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  1. Yang-Kuei Lin
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Lin, YK. Scheduling Identical Jobs on Uniform Parallel Machines Under Position-Based Learning Effects. Arab J Sci Eng 39, 6567–6574 (2014). https://doi.org/10.1007/s13369-014-1284-3

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  • DOI: https://doi.org/10.1007/s13369-014-1284-3

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