R
Reza Tavakkoli-Moghaddam
Researcher at University of Tehran
Publications - 724
Citations - 17195
Reza Tavakkoli-Moghaddam is an academic researcher from University of Tehran. The author has contributed to research in topics: Supply chain & Fuzzy logic. The author has an hindex of 56, co-authored 650 publications receiving 13200 citations. Previous affiliations of Reza Tavakkoli-Moghaddam include University of British Columbia & Education and Research Network.
Papers
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Journal ArticleDOI
A centroid opposition-based coral reefs algorithm for solving an automated guided vehicle routing problem with a recharging constraint
TL;DR: In this paper , a synchronization problem of task scheduling and AGV routing is studied on a shop floor with reconfigurable machine tools, where the objective is to minimize the maximum completion time (i.e., makespan) of all products.
Proceedings ArticleDOI
A capacitated location-routing problem with customer satisfaction under facility disruption
TL;DR: In this article, a hybrid NSGA-II algorithm is proposed and the related results are compared with the traditional NSGA II as a well-known evolutionary algorithm, the taguchi method is used to tune the best values of parameters to run the algorithms.
Book ChapterDOI
Integrated Workforce Allocation and Scheduling in a Reconfigurable Manufacturing System Considering Cloud Manufacturing
TL;DR: In this article, the authors investigated the advantage of using cloud manufacturing (CMfg) resources in enhancing the performance of an RMS system and developed a novel mathematical model for the integrated workforce allocation and production scheduling problem utilizing the CMfg under a non-permutation flow shop setting.
Journal ArticleDOI
A GENERALIZED CELL FORMATION PROBLEM IN DYNAMIC ENVIRONMENT WITH DIFFERENT INTER and INTRA-CELL BATCH SIZES
TL;DR: In this paper, a mixed-integer linear programming approach for cell formation problem (CFP) by assuming that the product mix and part demand change under a multi-period planning horizon is presented.
Proceedings ArticleDOI
Multi-objective Optimization for Mixed-model Assembly Line Sequencing and Balancing in the Context of Industry 4.0
TL;DR: In this article, a multiobjective mathematical model is proposed to solve the problem of line balancing in a mixed-model assembly line, and the augmented econstraint (AUGMECON) method is used to solve it.