Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem

Duman, Ekrem; Uysal, Mitat; Alkaya, Ali Fuat

doi:10.1016/j.ins.2012.06.032

Cited by 241 publications

(168 citation statements)

References 46 publications

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“…The algorithm AHA is chosen to compare with HLS. Besides, for the migrating birds optimization (MBO) [41], it is a metaheuristic inspired from the flight of migrating birds. To save the energy, the known V-flight shape3 is developed.…”

Section: Comparison Results With Some Recent Algorithmsmentioning

confidence: 99%

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

Wang

2017

Sustainability

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This paper focuses on the flowshop scheduling problem with sequence dependent setup times (FSSP-SDST), which has been an investigated object for decades as one of the most popular scheduling problems in manufacturing systems. A novel hybrid local search algorithm called HLS is presented to solve the flowshop scheduling problem with sequence dependent setup times with the criterion of minimizing the makespan. Firstly, the population is initialized by the Nawaz-Enscore-Hoam based problem-specific method (NEHBPS) to generate high quality individuals of the current population. Then, a global search embedded with a light perturbation is designed to produce a new population. After that, to improve the quality of individuals in the current population, a single insertion-based local search is applied. Meanwhile, a further local search strategy based on the insertion-based local search is used to find better solutions for the individuals which are non-improved. Finally, the heavy perturbation is used to explore potential solutions in the neighbor region. To validate the performance of HLS, we compare our proposed algorithm with other competitive algorithms on Taillard benchmark problems. From the experimental results, it can be concluded that the proposed algorithm outperforms the benchmark algorithms.

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Section: Comparison Results With Some Recent Algorithmsmentioning

confidence: 99%

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

Wang

2017

Sustainability

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“…The smallest position value (SPV) rule was developed to enable the continuous version of the particle swarm optimization algorithm to be applied to the permutation problems. Another special case of the nature-inspired algorithms, called migrating birds optimization algorithm (MBO), inspired by V-formation flight of migrating birds, was proposed and tested on quadratic assignment problems by Duman et al [27]. Chmiel et al in [3] presented the most important properties of a multi-population genetic algorithm.…”

Section: Algorithms For Qapmentioning

confidence: 99%

A comparison of nature inspired algorithms for the quadratic assignment problem

Chmiel

Kadłuczka

Kwiecień

et al. 2017

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. This paper presents an application of the ant algorithm and bees algorithm in optimization of QAP problem as an example of NPhard optimization problem. The experiments with two types of algorithms: the bees algorithm and the ant algorithm were performed for the test instances of the quadratic assignment problem from QAPLIB, designed by Burkard, Karisch and Rendl. On the basis of the experiments results, an influence of particular elements of algorithms, including neighbourhood size and neighbourhood search method, will be determined. The QAP is an NP-hard problem and this difficulty is not restricted only to finding the optimal solution. Sahni and Gonzalez [4] proved that even finding an ɛ-approximation solution for QAP is a hard problem in this sense that the existence of a ɛ-approximation algorithm implies P = NP.Finding an optimal solution to QAP is a difficult task not only in case of looking for the best solution among all the feasible ones. It might appear that finding an optimal solution in the subset of the feasible solutions can be easier. For QAP it was proven that finding an optimal solution in case of the local search is a difficult problem too. Johnson and Papadimitriou in [6] created the base for the complexity theory in the local search case, where a special structure of neighbourhood is introduced. They define the PLS-problems (polynomial-time local search problem) as a set for which a locally optimal solution can be found in polynomial time. Next, they introduce a PLS-complete decision problem as an analogy of NP-complete one, which are the most difficult problems in PLS.Murthy, Pardalos and Li [7] proposed a neighbourhood structure for QAP problem and proved that the corresponding local search problem is PLS-complete. The proposed structure is similar to that proposed by Kernighan and Lin [8] for the graph partitioning problem called K-L type neighbourhood structure N K-L . As the problem of finding QAP optimal solution in N K-L (called (QAP, N K-L )) is PLS-complete, then in the

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“…Migrating birds optimization (MBO) algorithm was proposed by Duman et al (2012). In MBO, it is assumed that after flying fro some time, when the leader birds gets tired, it goes to the end of the line and one of the birds following it takes the leader position.…”

Section: Fundamentals Of Migrating Birds Optimization Algorithmmentioning

confidence: 99%

“…As a result, MBO is capable of finding more areas of the feasible solution space by looking at the neighbour solutions. The main steps of MBO are outlined below (Duman et al 2012):…”

Section: Fundamentals Of Migrating Birds Optimization Algorithmmentioning

confidence: 99%

Emerging Biology-based CI Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, a group of (more specifically 56 in total) emerging biology-based computational intelligence (CI) algorithms are introduced. We first, in Sect. 17.1, describe the organizational structure of this chapter. Then, from Sects. 17.2 to 17.57, each section is dedicated to a specific algorithm which falls within this category, respectively. The fundamentals of each algorithm and their corresponding performances compared with other CI algorithms can be found in each associated section. Finally, the conclusions drawn in Sect. 17.58 closes this chapter.

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Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem

Cited by 241 publications

References 46 publications

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

A comparison of nature inspired algorithms for the quadratic assignment problem

Emerging Biology-based CI Algorithms

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