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Improving Approaches for Meta-heuristic Algorithms: A Brief Overview
2022Optimization problems can be observed in many applications, ranging from engineering applications and decision-making to computer science and finance. Optimization can be described as a process for discovering optimal solution among all available solutions of the defined problem, considering complex and high-dimensional constraints in searching for the
Arya Yaghoubzadeh-Bavandpour +3 more
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Metaheuristic algorithms represent a key area of optimization research that generates interest for many academicians and researchers in today's technology landscape. Researchers have been using these methods as a problem-solving approach for many decades when applied to combinatorial optimization problems, which has now grown into a significant ...
Arshiya Begum, Asfia Sabahath
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Arshiya Begum, Asfia Sabahath
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Meta-heuristic algorithms for wafer sorting scheduling problems
Journal of the Operational Research Society, 2011Wafer sorting is usually regarded as the most critical stage in the whole wafer probing process. This paper discusses the wafer sorting scheduling problem (WSSP) with total setup time minimization as the primary criterion and the minimization of the number of machines used as the secondary criterion.
Shih-Wei Lin +3 more
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Parking recommendation with meta-heuristic algorithms
Theoretical and Natural ScienceDue to the exponential growth of cars in urban areas, parking problems have become a significant concern. Addressing this issue requires efficient methods for locating available parking spaces, enhancing the overall experience for drivers. This paper introduces a parking lot recommendation model leveraging meta-heuristic algorithms to generate a list ...
Siyuan Wu, Tingting Yang
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Introduction to Meta-heuristic Optimization Algorithms
2019This chapter begins with a concise definition of the optimization problem and its parameters, along with a mathematical description of an optimization problem with continuous and discrete decision-making variables whose objective functions are employed in a standard form of an optimization problem along with equality and inequality constraints ...
Mohammad Kiani-Moghaddam +2 more
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Boxing Match Algorithm: a new meta-heuristic algorithm
Soft Computing, 2022Mehrab Tanhaeean +2 more
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Genetic Algorithm and Other Meta-Heuristics
2005Genetic algorithms have been applied in solving various types of large-scale, NP-hard optimization problems. Many researchers have been investigating its global convergence properties using Schema Theory, Markov Chain, etc. A more realistic approach, however, is to estimate the probability of success in finding the global optimal solution within a ...
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Local search and meta-heuristic algorithms
2020Suboptimal schedules for intractable time-dependent scheduling problems may be found by using various algorithms. In this chapter, closing the fifth part of the book, we consider local search and meta-heuristic algorithms.
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Metrics for meta-heuristic algorithm evaluation
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2004By adopting best practices from quality management in industry, metrics as well as test cycle are proposed to evaluate the performance of meta-heuristic algorithm.
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Competitive Learning: A New Meta-Heuristic Optimization Algorithm
International Journal on Artificial Intelligence Tools, 2018This work proposes a new powerful meta-heuristic optimization algorithm in education process called Competitive Learning (CLA). The algorithm is benchmarked on 8 well-known test functions, and the results are verified by a comparative study with some meta-heuristic optimization methods including: Imperialist Competitive Algorithm (ICA), Teaching ...
Afshin Afroughinia +1 more
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