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The Design and Development of a Modified Artificial Bee Colony Approach for the Traveling Thief Problem

The Design and Development of a Modified Artificial Bee Colony Approach for the Traveling Thief Problem

Saad T. Alharbi
Copyright: © 2018 |Volume: 9 |Issue: 3 |Pages: 16
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781522544166|DOI: 10.4018/IJAEC.2018070104
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MLA

Alharbi, Saad T. "The Design and Development of a Modified Artificial Bee Colony Approach for the Traveling Thief Problem." IJAEC vol.9, no.3 2018: pp.32-47. http://doi.org/10.4018/IJAEC.2018070104

APA

Alharbi, S. T. (2018). The Design and Development of a Modified Artificial Bee Colony Approach for the Traveling Thief Problem. International Journal of Applied Evolutionary Computation (IJAEC), 9(3), 32-47. http://doi.org/10.4018/IJAEC.2018070104

Chicago

Alharbi, Saad T. "The Design and Development of a Modified Artificial Bee Colony Approach for the Traveling Thief Problem," International Journal of Applied Evolutionary Computation (IJAEC) 9, no.3: 32-47. http://doi.org/10.4018/IJAEC.2018070104

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Abstract

The traveling thief problem (TTP) is a benchmark problem that consists of two well-known problems, the traveling salesman problem (TSP) and the knapsack problem (KP). It was defined to imitate complex real-world applications that comprise different interdependent sub-problems. Various approaches were proposed in the literature to solve such a problem. These approaches mostly focus on local search algorithms, heuristics methods and evolutionary approaches. In addition, some of these approaches concentrated on solving the problem by considering each sub-problem independently. Thus far, limited approaches were proposed to solve the problem using swarm intelligence. In this article, the authors introduce a modified artificial bees colony (ABC) algorithm that addresses the TTP in an interdependent manner. The performance of this approach was compared with various recent approaches in the literature using different benchmark instances. The obtained results demonstrated that it is competitive with the state-of-the-art approaches, especially on small and medium instances.

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