Researcher:
Fattahi, Ali

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Master Student

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Ali

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Fattahi

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Fattahi, Ali

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2014 - 20153

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Researcher Of Publications: search.filters.isAuthorOfPublication.37f93054-0420-44b7-94e4-88faa29fb501

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    A novel integer programming formulation with logic cuts for the U-shaped assembly line balancing problem
    (Taylor and Francis, 2014) Elaoud, Semya; Azer, Erfan Sadeqi; N/A; Department of Industrial Engineering; Department of Industrial Engineering; Fattahi, Ali; Türkay, Metin; Master Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956
    U-shaped assembly lines are regarded as an efficient configuration in Just-In-Time manufacturing. Balancing the workload in these lines is an unsolved problem that attracted significant research within the past two decades. We present a novel integer programming formulation for U-shaped line balancing problems, where cycle time, the interval between two consecutive outputs, is known and the aim is to minimize the number of workstations. To enhance the efficiency of the LP relaxation of the new formulation, we present three types of logic cuts (assignable-station-cuts, task-assignment-cuts and knapsack-cuts) that exploit the inherent logic of the problem structure. The new formulation and logic cuts are tested on an extensive set of benchmark problems to provide a comparative analysis with the existing models in the literature. The results show that our novel formulation augmented by assignable-station-cuts is significantly better than the previous formulations.
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    On the milp model for the u-shaped assembly line balancing problems
    (Elsevier, 2015) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Fattahi, Ali; Türkay, Metin; Master Student; Faculty Member; N/A; College of Engineering; N/A; 24956
    U-shaped assembly lines are an important configuration of modern manufacturing systems due to their flexibility to adapt to varying market demands. In U-shaped lines, tasks are assigned after their predecessors or successors. Some MILP models have been proposed to formulate the U-shaped assembly line balancing problem using either-or constraints to express precedence relationships. We show that this modeling approach reported in the literature may often find optimal solutions that are infeasible and verify this on a large set of benchmark problems. We present a revision to this model to accurately express the precedence relationships without introducing additional variables or constraints. We also illustrate on the same benchmark problems that our revision always reports solutions that are feasible. (C) 2014 Elsevier B.V. All rights reserved.
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    ε-OA for the solution of bi-objective generalized disjunctive programming problems in the synthesis of nonlinear process networks
    (Pergamon-Elsevier Science Ltd, 2015) N/A; Department of Industrial Engineering; Department of Industrial Engineering; Fattahi, Ali; Türkay, Metin; Master Student; Faculty Member; N/A; College of Engineering; N/A; 24956
    There has been an increasing interest in multicriteria optimization (MCO) of nonlinear process network problems in recent years. Several mathematical models have been developed and solved using MCO methodologies including e-constraint, weighted sum, and minimum distance. In this paper, we investigate the bi-objective nonlinear network synthesis problem and propose an effective algorithm, epsilon-OA, based on augmented epsilon-constraint and logic-based outer approximation (OA). We provide theoretical characterization of the proposed algorithm and show that the solutions generated are efficient. We illustrate the effectiveness of our novel algorithm on two benchmark problems. The epsilon-OA is compared to the straightforward use of OA with augmented epsilon-constraint algorithm (epsilon-con + OA), the augmented epsilon-constraint without OA (E-MINLP), and the traditional epsilon-constraint (T-epsilon-con). Based on the results, our novel algorithm is very effective in solving the bi-objective generalized disjunctive programming problems in the synthesis of process networks. (C) 2014 Elsevier Ltd. All rights reserved.