A discrete binary version of bat algorithm for multidimensional knapsack problem

Sabba, Sara; Chikhi, Salim

doi:10.1504/ijbic.2014.060598

Cited by 58 publications

(10 citation statements)

References 30 publications

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“…The earlier studies have shown that BA can solve constrained and unconstrained optimization problems with superior efficiency and robustness [20,21]. Although BA was proposed recently, there are many variants of BA that have been successfully applied to different fields and problems, such as the traveling salesman problem [22,23], vehicle routing problem [24,25], 0-1 knapsack problem [26,27], and unmanned aerial vehicle path planning problem [28]. Hence, the BA is applied in this work.…”

Section: Bat Algorithmmentioning

confidence: 99%

Simultaneous Optimisation of Cable Connection Schemes and Capacity for Offshore Wind Farms via a Modified Bat Algorithm

Hou

Yang

et al. 2019

Applied Sciences

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Offshore wind energy has attracted worldwide attention and investments in the last decade due to the stability and abundance of wind resources. As one of the main components of this, internal array cables have a great impact on the levelised cost of energy of offshore wind farms, and thus their connection layout is a matter of concern. In this paper, a classical mathematical problem—the traveling salesman problem, which belongs to the field of graph theory—is applied to solve the offshore wind farm cable connection layout optimization problem. Both the capital investment on cables, cable laying, and the cost of power losses associated with array cables are considered in the proposed model. A modified bat algorithm is presented to resolve the problem. Furthermore, a cable crossing detection method is also adopted to avoid obtaining crossed cable connection layouts. The effectiveness was verified through a case study.

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Section: Bat Algorithmmentioning

confidence: 99%

Simultaneous Optimisation of Cable Connection Schemes and Capacity for Offshore Wind Farms via a Modified Bat Algorithm

Hou

Yang

et al. 2019

Applied Sciences

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“…Towards the solution of binary space's optimization problem, S. Sabba et al [29] inaugurated discrete binary bat algorithm (BinBA). The sigmoid function is embedded in proposed algorithm, which implemented by Kennedy in 1997 for binary PSO.…”

Section: Mutation Strategiesmentioning

confidence: 99%

An Overview of Mutation Strategies in Bat Algorithm

Bangyal¹,

Ahmad²,

Tayyab³

et al. 2018

ijacsa

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Abstract-Bat algorithm (BA) is a population based stochastic search technique encouraged from the intrinsic manner of bee swarm seeking for their food source. BA has been mostly used to resolve diverse kind of optimization problems and one of major issue faced by BA is frequently captured in local optima meanwhile handling the complex real world problems. Many authors improved the standard BA with different mutation strategies but an exhausted comprehensive overview about mutation strategies is still lacking. This paper aims to furnish a concise and comprehensive study of problems and challenges that prevent the performance of BA. It has been tried to provide guidelines for the researchers who are active in the area of BA and its mutation strategies. The objective of this study is divided in two sections: primarily to display the improvement of BA with mutation strategies that may enhance the performance of standard BA up to great extent and secondly, to motivate the researchers and developers for using BA to solve the complex real world problems. This study presents a comprehensive survey of the various BA algorithms based on mutation strategies. It is anticipated that this survey would be helpful to study the BA algorithm in detail for the researcher.

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“…A few years ago, some recent research focused on BA in combinatorial optimization problems, such as Xie et al [56] introduced a differential Lévy-flights BA to minimize the permutation flow shop problem. Sabba and Chikhi [57] used the sigmoid function to propose a discrete binary BA for solving the multidimensional knapsack problem. Büyüksaatçı [58] used BA to solve the single-row facility layout problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel discrete bat algorithm for solving the travelling salesman problem

Saji

Riffi

2015

Neural Comput & Applic

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The travelling salesman problem (TSP) is one of the well-known NP-hard combinatorial optimization and extensively studied problems in discrete optimization. The bat algorithm is a new nature-inspired metaheuristic optimization algorithm introduced by Yang in 2010, especially based on echolocation behavior of microbats when searching their prey. Firstly, this algorithm is used to solve various continuous optimization problems. In this paper we extend a discrete bat-inspired algorithm to solve the famous TSP. Although many algorithms have been used to solve TSP, the main objective of this research is to investigate this discrete version to achieve significant improvements, not only compared to traditional algorithms but also to another metaheuristics. Moreover, this study is based on a benchmark dataset of symmetric TSP from TSPLIB library.Keywords Travelling salesman problem Á NP-hard combinatorial optimization problem Á Nature-inspired metaheuristic Á Discrete bat-inspired algorithm

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A discrete binary version of bat algorithm for multidimensional knapsack problem

Cited by 58 publications

References 30 publications

Simultaneous Optimisation of Cable Connection Schemes and Capacity for Offshore Wind Farms via a Modified Bat Algorithm

Simultaneous Optimisation of Cable Connection Schemes and Capacity for Offshore Wind Farms via a Modified Bat Algorithm

An Overview of Mutation Strategies in Bat Algorithm

A novel discrete bat algorithm for solving the travelling salesman problem

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