Animal Migration Optimization Algorithm for Constrained Engineering Optimization Problems

Zhou, Yongquan; Luo, Qifang; Ma, Mingzhi; Qiao, Shilei; Bao, Zongfan

doi:10.1166/jctn.2016.4838

Cited by 3 publications

(1 citation statement)

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“…It is observed that IAMO outperforms all the analyzed algorithms for certain clustering problems. Another study researched constrained engineering optimization problems [13]. This improved algorithm is called the fast convergence AMO algorithm and it is based on reducing the search space of animals dynamically.…”

Section: Introductionmentioning

confidence: 99%

An elitist approach for solving the traveling salesman problem using an animal migration optimization algorithm

Ülker¹

2018

Turk J Elec Eng & Comp Sci

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This paper presents an improved version of the animal migration optimization (AMO) algorithm for solving the traveling salesman problem (TSP), which is classified as a combinatorial NP-hard problem. AMO is one of the recent metaheuristic algorithms inspired by the migration behavior of animals and has been efficiently applied to a variety of optimization problems. The algorithm is improved by reconstructing the neighborhood topology of each animal during the migration. This modified algorithm is called the elitist animal migration optimization (ELAMO) algorithm, since elitism is introduced as a way in which the positions of the leaders are considered for the neighborhood scheme. To observe the performance of ELAMO, it is compared with AMO and some efficient algorithms. The experimental results showed that the ELAMO algorithm has improved the solution quality of AMO and has produced effective or even competitive values for the selected TSP data sets.

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Section: Introductionmentioning

confidence: 99%

An elitist approach for solving the traveling salesman problem using an animal migration optimization algorithm

Ülker¹

2018

Turk J Elec Eng & Comp Sci

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Animal migration optimization algorithm: novel optimizer, analysis, and applications

Abualigah,

Ahmad,

Ikotun

et al. 2024

Metaheuristic Optimization Algorithms

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A discrete animal migration algorithm for dual-resource constrained energy-saving flexible job shop scheduling problem

Jiang

Zhu

et al. 2022

IFS

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This paper presents a discrete animal migration optimization (DAMO) to solve the dual-resource constrained energy-saving flexible job shop scheduling problem (DRCESFJSP), with the aim of minimizing the total energy consumption in the workshop. A job-resource-based two-vector encoding method is designed to represent the scheduling solution, and an energy-saving decoding approach is given based on the left-shift rule. To ensure the quality and diversity of initial scheduling solutions, a heuristic approach is employed for the resource assignment, and some dispatching rules are applied to acquire the operation permutation. In the proposed DAMO, based on the characteristics of the DRCESFJSP problem, the search operators of the basic AMO are discretized to adapt to the problem under study. An animal migration operator is presented based on six problem-based neighborhood structures, which dynamically changes the search scale of each animal according to its solution quality. An individual updating operator based on crossover operation is designed to obtain new individuals through the crossover operation between the current individual and the best individual or a random individual. To evaluate the performance of the proposed algorithm, the Taguchi design of experiment method is first applied to obtain the best combination of parameters. Numerical experiments are carried out based on 32 instances in the existing literature. Computational data and statistical comparisons indicate that both the left-shift decoding rule and population initialization strategy are effective in enhancing the quality of the scheduling solutions. It also demonstrate that the proposed DAMO has advantages against other compared algorithms in terms of the solving accuracy for solving the DRCESFJSP.

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Animal Migration Optimization Algorithm for Constrained Engineering Optimization Problems

Cited by 3 publications

References 0 publications

An elitist approach for solving the traveling salesman problem using an animal migration optimization algorithm

An elitist approach for solving the traveling salesman problem using an animal migration optimization algorithm

Animal migration optimization algorithm: novel optimizer, analysis, and applications

A discrete animal migration algorithm for dual-resource constrained energy-saving flexible job shop scheduling problem

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