M
Mostafa Zandieh
Researcher at Shahid Beheshti University
Publications - 224
Citations - 7961
Mostafa Zandieh is an academic researcher from Shahid Beheshti University. The author has contributed to research in topics: Job shop scheduling & Flow shop scheduling. The author has an hindex of 50, co-authored 214 publications receiving 6877 citations. Previous affiliations of Mostafa Zandieh include K.N.Toosi University of Technology & Mazandaran University of Science and Technology.
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An artificial immune algorithm for the flexible job-shop scheduling problem
TL;DR: An artificial immune algorithm (AIA) based on integrated approach is proposed to solve the flexible job-shop scheduling problem (FJSP) to minimize makespan and the computational results validate the quality of the proposed approach.
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An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times
TL;DR: An immune algorithm approach to the scheduling of a SDST hybrid flow shop is described and it was established that IA outperformed RKGA.
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Flexible job-shop scheduling with parallel variable neighborhood search algorithm
TL;DR: A parallel variable neighborhood search (PVNS) algorithm that solves the FJSP to minimize makespan time and uses various neighborhood structures which carry the responsibility of making changes in assignment and sequencing of operations for generating neighboring solutions.
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Scheduling trucks in cross-docking systems: Robust meta-heuristics
Behnam Vahdani,Mostafa Zandieh +1 more
TL;DR: Five meta-heuristic algorithms are applied to schedule the trucks in cross-dock systems such that minimize total operation time when a temporary storage buffer to hold items temporarily is located at the shipping dock.
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An improved simulated annealing for hybrid flowshops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness
TL;DR: A metaheuristic based on simulated annealing which strikes a compromise between intensification and diversification mechanisms to augment the competitive performance of the proposed SA is applied.