Abstract
Ant colony system (ACS) has been widely applied for solving discrete domain problems in recent years. In particular, they are efficient and effective in finding nearly optimal solutions to discrete search spaces. Because of the restriction of ant-based algorithms, when the solution space of a problem to be solved is continuous, it is not so appropriate to use the original ACS to solve it. However, engineering mathematics in the real applications are always applied in the continuous domain. This paper thus proposes an extended ACS approach based on binary-coding to provide a standard process for solving problems with continuous variables. It first encodes solution space for continuous domain into a discrete binary-coding space (searching map), and a modified ACS can be applied to find the solution. Each selected edge in a complete path represents a part of a candidate solution. Different from the previous ant-based algorithms for continuous domain, the proposed binary coding ACS (BCACS) could retain the original operators and keep the benefits and characteristics of the traditional ACS. Besides, the proposed approach is easy to implement and could be applied in different kinds of problems in addition to mathematical problems. Several constrained functions are also evaluated to demonstrate the performance of the proposed algorithm.
Highlights
Ant colony systems (ACS) have been shown to have good performance in finding near-optimal solutions for NP-hard problems
Experiments were made to show the performance of the proposed binary coding ACS (BCACS)
BCACS was compared to some existing approaches including API [11], genetic algorithms (GAs), and CACS [7]
Summary
Ant colony systems (ACS) have been shown to have good performance in finding near-optimal solutions for NP-hard problems. An ACS adopts distributed computation and uses a constructive greedy strategy [1] with positive feedback to search for solutions. It is a powerful approach inspired by the behavior of ants, which deposit chemical trails (pheromone) on the ground to communicate with each other. ACS algorithms have been used to discover good solutions to many applications [2,3,4,5,6]. They are adopted to solve algebraic equations in mathematics [7]
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