Department of Management

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Author: search.filters.author.Matai, RajeshSubject: search.filters.subject.Heuristic

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    Non-greedy systematic neighbourhood search heuristic for multi-objective facility layout problem
    (Inder Science, 2012-05) Matai, Rajesh
    In this paper a non-greedy systematic neighbourhood search heuristic is presented for solving multi-objective facility layout problem. It can incorporate more than two objectives that may be qualitative or quantitative in nature. Computational results show superiority of our proposed heuristic algorithm than other algorithms available in literature. Finally, comparison was also made with best solution qualities for the 15 single objective test problems of Nugxx series taken from QAPLIB and this comparison also shows efficiency and effectiveness of proposed heuristic algorithm.
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    A new heuristic approach for solving facility layout problem
    (Inder Science, 2013-04) Matai, Rajesh
    This paper proposes a new heuristic approach for solving facility layout problem (FLP) which is traditionally formulated as quadratic assignment problem (QAP). In this paper, FLP is formulated as linear assignment problem (LAP) consisting of facility pair and location pair. Being linear in nature LAP can be solved efficiently. Solution of LAP provides lower bound on corresponding QAP formulation of FLP. Heuristic procedure is applied to solve FLP from sets of LAP solution. Proposed heuristic is tested on benchmark instances taken from literature and compared with other heuristics available in literature. Computational results show that proposed heuristic provides a good quality approximate solution. This solution can be taken as initial solution for any improvement heuristic to get optimal/near optimal solution for FLP.
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    A non-greedy systematic neighbourhood search heuristic for solving facility layout problem
    (Springer, 2013-05) Matai, Rajesh
    This paper presents a new heuristic for solving a facility layout problem. The proposed heuristic works on the non-greedy systematic pairwise exchange of two facilities, that is 2-exchange neighbourhood search based on non-greedy strategy. The proposed heuristic is applied on a large number of test problems provided by different authors in the quadratic assignment problem (QAP) library (Burkard, Karisch, Rendl, J Glob Optim 10(1):391–403, 1997) with problem size ranging from 12 to 256. Out of the 135 test problems available in the QAP library, the proposed heuristic reached optimal solutions for 64 test problems and matched the best known available solution for the other 15 test problems. For the remaining 56 test problems, the proposed approach reports highly encouraging solutions for 44 test problems (within the 2 % of deviation from the optimal/best known solutions), and for the remaining 12 problems, the proposed approach provides fair solution in reasonable time. Comparison with other meta-heuristic approaches (Ro-TS, RE-TS, GEN and SA) shows the effectiveness of the proposed heuristic.
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    Solving multi objective facility layout problem by modified simulated annealing
    (Elsevier, 2015-06) Matai, Rajesh
    This paper proposes a modified simulated annealing approach for solving multi objective facility layout problem. Multi objective facility layout problem is solved by using different objective weights which are generated by decision maker. Thus layout design process is decision maker dependent. However proposed approach in this paper makes layout design process independent of decision maker. Proposed approach can also incorporate any number of objectives that may be qualitative or quantitative in nature. Computational results show superiority of proposed heuristic approach than other approaches available in literature. Finally, comparison was also made with best solution qualities for the 15 single objective test problems of Nugxx series taken from QAPLIB. Comparisons were made in terms of the quality of the solutions obtained and the computational time required and this comparison shows efficiency and effectiveness of proposed modified simulated annealing algorithm.