STM Journals Peer-reviewed research from Consortium e-Learning Network

3 publications

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    Evolutionary Optimization in MPS: A Brief Review

    By S. Radhika, Ch. Srinivasa Rao, K. Lakshmi Chaitanya, M. Vijaya

    Abstract: Master production scheduling (MPS) is a combinatorial optimization problem that arises frequently in real-life applications. Because of the complexity and the vast search space, conventional optimization methods such as mathematical programming, dynamic programming and branch-and-bound technique are computationally infeasible. Evolutionary approach-based meta-heuristics have gained prominence in recent years for solving multi-objective optimization problems (MOP). Multi-objective evolutionary approaches (MOEAs) have substantial success across a variety of real-world engineering applications. The present …

    Published in Journal of Production Research & Management · Vol. 4, Issue 1, 2014 · pp. 13–21 Read article

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    VIKOR Method for Multi Criteria Decision Making in Academic Staff Selection

    By S. Radhika, D.Sameer Kumar, D. Swapna

    Abstract: For any academic organization, the selection of qualified personnel is a key success factor. As many factors such as professional ability, communication ability, work experience and so on influence the personnel selection, this becomes a Multi Criteria Decision Making (MCDM) problem. MCDM methods provide a ranking of the available alternatives thereby, decision of critical thinking become easier. A branch of MCDM methods named Vlse Kriterijumska Optimizacija I Kompromisno Resenje in …

    Published in Journal of Production Research & Management · Vol. 3, Issue 2, 2013 · pp. 30–35 Read article

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    A Study and Performance Evaluation of Evolutionary Optimization Techniques for Multi-objective Master Production Scheduling Problems

    By S. Radhika, Ch. Srinivasa Rao, K. Karteeka Pavan

    Abstract: Master production schedule (MPS) can effectively and efficiently synchronize the operations in any organization. MPS, which is posed as one of the multi-objective parameter optimization problems, is a plan that determines optimal values of products to be produced. For many engineering optimization problems, more competitive and optimal solutions can be obtained by using Heuristic evolutionary optimization algorithms. Among these, two main algorithms considered here are the differential evolution (DE) whose …

    Published in Journal of Production Research & Management · Vol. 3, Issue 2, 2013 · pp. 12–22 Read article

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