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5 articles for “combinatorial optimization”
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Job Shop and Flexible Job Shop Scheduling Problems: Heuristic Optimization
Abstract: The development of modern wide-area engineering problems, as well as recent trends towards the creation of sustainable engineering systems for daily objectives have given birth to complex studies addressing technical, but also economical and environmental, aspects related to simple or multi-objective optimization problems. Recently, heuristic and (meta) heuristic approachesthat apply combinations of different heuristics with or without traditional search and optimization techniques were proposed to solve such problems. This paper …
Published in Journal of Production Research & Management · Vol. 10, Issue 1, 2020 · pp. 25–31 Read article
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Evolutionary Optimization in MPS: A Brief Review
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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A Review: Application of Ant Algorithm in Transport Network Design Problems
Abstract: A dependable and reliable information source for transportation route planning and ready response to traveler demand, have become a hot topic of research these days. Transportation route planning, analysis and processing of traveler demand are among most important factors affecting response to traveler demand. Because of highly dynamic networks and frequent discontinuity, it is desirable to establish routes for fast delivery of people and goods, having a low probability of …
Published in Trends in Transport Engineering and Applications · Vol. 3, Issue 3, 2016 · pp. 17–22 Read article
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Generation Scheduling Using Quantum Inspired Evolutionary Programming
Abstract: A new novel evolutionary algorithm based on principles of quantum mechanics known as quantum inspired evolutionary programming (QIEP) has emerged as a modern optimization technique. QIEP is unique than other evolutionary programming for its qubit representation and superposition of states. QIEP has proven its applicability in different combinatorial problems successfully. It can also be applied in power system optimization problem. In this paper, we have used QIEP for generation scheduling. …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 12–15 Read article
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Remote Sensing Classification Based on Improve Ant-Miner Algorithm: A Case Study of Alwar, Rajasthan, India
Abstract: Earth Observation Satellite (EOS) image itself contains image ambiguity. Various conventional methods like minimum distance to mean or maximum likelihood image clustering algorithm do not meet the accuracy that have required by user in the virtue of cost-effective land use/land cover classification. In Ant colony optimization (ACO), association rule mining is a prevalent and well researched method for discovering useful relations between variables in large databases. The proposed work presents …
Published in Journal of Geotechnical Engineering · Vol. 2, Issue 3, 2015 · pp. 1–5 Read article