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DisABC: A new artificial bee colony algorithm for binary optimization

机译：DisABC：一种用于二进制优化的新人工蜂群算法

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摘要

Artificial bee colony (ABC) algorithm is one of the recently proposed swarm intelligence based algorithms for continuous optimization. Therefore it is not possible to use the original ABC algorithm directly to optimize binary structured problems. In this paper we introduce a new version of ABC, called DisABC, which is particularly designed for binary optimization. DisABC uses a new differential expression, which employs a measure of dissimilarity between binary vectors in place of the vector subtraction operator typically used in the original ABC algorithm. Such an expression helps to maintain the major characteristics of the original one and is respondent to the structure of binary optimization problems, too. Similar to original ABC algorithm, DisABC's differential expression works in continuous space while its consequence is used in a two-phase heuristic to construct a complete solution in binary space. Effectiveness of DisABC algorithm is tested on solving the uncapacitated facility location problem (UFLP). A set of 15 benchmark test problem instances of UFLP are adopted from OR-Library and solved by the proposed algorithm. Results are compared with two other state of the art binary optimization algorithms, i.e., binDE and PSO algorithms, in terms of three quality indices. Comparisons indicate that DisABC performs very well and can be regarded as a promising method for solving wide class of binary optimization problems.
机译：人工蜂群（ABC）算法是最近提出的基于群体智能的算法，用于连续优化。因此，不可能直接使用原始的ABC算法来优化二进制结构化问题。在本文中，我们介绍了一种新版本的ABC，称为DisABC，它是专门为二进制优化设计的。 DisABC使用了一种新的差分表达式，该差分表达式采用了二进制矢量之间的相异度度量来代替原始ABC算法中通常使用的矢量减法运算符。这样的表达式有助于保持原始表达式的主要特征，并且也响应于二进制优化问题的结构。与原始ABC算法相似，DisABC的差分表达式可在连续空间中工作，而其结果可用于两阶段启发式算法，从而在二进制空间中构造完整的解决方案。测试了DisABC算法在解决无能力设施位置问题（UFLP）方面的有效性。从OR-Library中选取了15个UFLP基准测试问题实例，并通过所提出的算法进行求解。就三个质量指标而言，将结果与其他两种最新的二进制优化算法（即binDE和PSO算法）进行比较。比较表明，DisABC的性能非常好，可以被认为是解决广泛的二进制优化问题的有前途的方法。

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