Permutation flowshop problems with bi-criterion makespan and total completion time objective and position-weighted learning effects |
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| Affiliation: | 1. Mechanical Engineering Department, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec H3C 1K3, Canada;2. Automated Production Engineering Department, Ecole de Technologie Superieure, 1100 Notre Dame West, Montreal, Quebec H3C 1K3, Canada;1. Department of Applied Math I, University of Seville, Spain;2. Department of Statistics and Operational Research, University of Seville, Spain;1. Ghent University, Department of Electrical Energy, Metals, Mechanical Constructions and Systems, Dynamical Systems and Control Laboratory, Technologiepark 914, 9000 Ghent, Belgium;2. University of Liege, Energy Systems Research Unit, Thermodynamics Laboratory, Campus du Sart Tilman B49, 4000 Lige, Belgium;3. Ghent University, Department of Flow, Heat and Combustion Mechanics, Graaf Karel de Goedelaan 5, 8500 Kortrijk, Belgium;4. Universidad de Ibagué, Facultad de Ingeniería, Programa de Ingeniería Electrónica, Carrera 22 Calle 67, 730001 Ibagué, Colombia |
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| Abstract: | In this paper, we study the problem of minimizing the weighted sum of makespan and total completion time in a permutation flowshop where the processing times are supposed to vary according to learning effects. The processing time of a job is a function of the sum of the logarithms of the processing times of the jobs already processed and its position in the sequence. We present heuristic algorithms, which are modified from the optimal schedules for the corresponding single machine scheduling problem and analyze their worst-case error bound. We also adopt an existing algorithm as well as a branch-and-bound algorithm for the general m-machine permutation flowshop problem. For evaluation of the performance of the algorithms, computational experiments are performed on randomly generated test problems. |
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| Keywords: | Scheduling Flowshop Learning effect Heuristic algorithm Branch-and-bound algorithm |
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