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A new meta-heuristic butterfly-inspired algorithm
Journal of Computational Science, 2017Abstract This paper proposes a novel bio-inspired algorithm named Artificial Butterfly Optimization (ABO) algorithm. The new algorithm is based on the mate-finding strategy of some butterfly species. Two groups of artificial butterflies are employed for simulating the flight strategies. If the flight strategies of artificial butterflies are redefined,
Xiangbo Qi, Yunlong Zhu, Hao Zhang 0017
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Cooperative meta-heuristic algorithms for global optimization problems
Expert Systems with Applications, 2021Abstract This paper presents an alternative global optimization meta-heuristics (MHs) approach, inspired by the natural selection theory. The proposed approach depends on the competition among six MHs that allows generating an offspring, which can breed the high characteristics of parents since they are unique and competitive.
Mohamed Abd El-Aziz 0001 +5 more
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Aquila Optimizer: A novel meta-heuristic optimization algorithm
Computers & Industrial Engineering, 2021Abstract This paper proposes a novel population-based optimization method, called Aquila Optimizer (AO), which is inspired by the Aquila’s behaviors in nature during the process of catching the prey. Hence, the optimization procedures of the proposed AO algorithm are represented in four methods; selecting the search space by high soar with the ...
Laith Mohammad Abualigah +5 more
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Randomization and Complex Networks for Meta-Heuristic Algorithms
2017This chapter deals with the hybridization of the chaos driven heuristics concept and complex networks framework for meta-heuristic. This research aims on the experimental investigations on the time development and influence of different randomization types, different strategies for Differential Evolution (DE) through the analysis of complex network as ...
Šenkeřík, Roman +5 more
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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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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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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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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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