An Improved Chaotic Bat Algorithm for Solving Integer Programming Problems

Raouf, Osama Abdel; Baset, Mohamed Abdel; Henawy, Ibrahim El

doi:10.5815/ijmecs.2014.08.03

Cited by 26 publications

(4 citation statements)

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“…Among other applications, fuzzy mathematics based BA is practiced with dynamic selection of parameters while execution (Perez, et al, 2015). Chaotic BAs are exploited by some researchers in various works (Lin, et al, 2012);(Abdel-Raouf, et al, 2014); (Gandomi & Yang, 2014). Ref.…”

Section: Methodsmentioning

confidence: 99%

Deploying NSBA algorithm for bi-objective manufacturing cells considering percentage utilisation of machines

Martinsen

Ghosh

2020

IJISTA

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Percentage Utilization of Machines is considered as an important production factor for manufacturing Cell Formation Problem (CFP) in Cellular Manufacturing (CM). This recently developed concept correctly emphasize ration data in context of CM. In this paper, a utilization based bi-objective mathematical model is developed, which minimizes the total machine utilization induced by bottleneck machines and number of voids. Thereafter, a new data generating algorithm is introduced. The abovementioned bi-objective CFP is solved using a Non-Dominated Sorting Bat Algorithm (NSBA), which is compared with published Multi-Objective Bat Algorithm (MOBA) successfully. Statistical tests are conducted and data consistency is confirmed on obtained results. The computational experiments depict that the Pareto solutions of NSBA are 35.7% improved. The contribution of this research is threefold. First, an accurate bi-objective mathematical expression is developed for utilization based CFPs. Second, a novel data generating algorithm is stated. Third, NSBA technique is successfully tested.

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Section: Methodsmentioning

confidence: 99%

Deploying NSBA algorithm for bi-objective manufacturing cells considering percentage utilisation of machines

Martinsen

Ghosh

2020

IJISTA

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“…Marichelvam et al [18,19] introduced the smallest position value (SPV) rule to transform the continuous position into discrete process sequences in BA for solving mixed flow shop scheduling problem. Abdel-Raouf et al [1] proposed an improved chaotic bat algorithm for solving integer programming problems. They use a chaotic map to replace the random number , and change the velocity function.…”

Section: Related Workmentioning

confidence: 99%

An Improved Unordered Pair Bat Algorithm for Solving the Symmetrical Traveling Salesman Problem

Zhang

Qiao

et al. 2022

Foundations of Computing and Decision Sciences

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Bat algorithm is an effective swarm intelligence optimization algorithm which is widely used to solve continuous optimization problems. But it still has some limitations in search process and can’t solve discrete optimization problems directly. Therefore, this paper introduces an unordered pair and proposes an unordered pair bat algorithm (UPBA) to make it more suitable for solving symmetric discrete traveling salesman problems. To verify the effectiveness of this method, the algorithm has been tested on 23 symmetric benchmarks and compared its performance with other algorithms. The results have shown that the proposed UPBA outperforms all the other alternatives significantly in most cases.

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“…In the full darkness, bat has a skill to discover its prey and diagnoses different kinds of insects. In most of the cases they exploit, short frequency signals to evaluate the object [29].…”

Section: Procedurementioning

confidence: 99%

A Method of A-BAT Algorithm Based Query Optimization for Crowd Sourcing System

Cincy¹,

Jeba²

2018

IJISA

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Abstract-In the field of database administration query optimization is one of the refinement processes. In recent years, huge volumes of data are flooded from different resources, which make query optimization, a difficult task for the researchers. In the crowd sourcing, environment query optimization is the biggest problem. The client is simply required to post an SQL-like subject, and the framework assumes the main issue of organizing the inquiry; execution setup is generated and in the crowd sourcing market places the evaluation plan evaluated. In order to retrieve data fast and reduce query processing time, Query optimization is badly required. In order to optimize the queries, Meta heuristic techniques are used. In this proposed paper, preprocessing method is used to mine the information from the Crowd. The Original population based ABC algorithm has low convergence speed. In this paper a novel A-BAT algorithm is proposed, which highly improve convergence speed, accuracy and Latency. This algorithm uses a Random walk phase. The proposed algorithm had better optimization accuracy, convergence rate, and robustness.

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An Improved Chaotic Bat Algorithm for Solving Integer Programming Problems

Cited by 26 publications

References 50 publications

Deploying NSBA algorithm for bi-objective manufacturing cells considering percentage utilisation of machines

Deploying NSBA algorithm for bi-objective manufacturing cells considering percentage utilisation of machines

An Improved Unordered Pair Bat Algorithm for Solving the Symmetrical Traveling Salesman Problem

A Method of A-BAT Algorithm Based Query Optimization for Crowd Sourcing System

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