Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm
Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm
复制标题
DOI：
10.3233/ifs-2010-0464
复制
发表时间：
2010-08
期刊：
影响因子：
--
通讯作者：
Lale Özbakır;Pinar Tapkan
中科院分区：
文献类型：
--
作者：
Lale Özbakır;Pinar Tapkan
现实生活中的许多问题都包含不精确的变量、约束和目标。在这种情况下，模糊集合理论提供了一个处理不精确术语的机会。双面装配线平衡（2sALB）问题是众所周知的简单装配线平衡问题的推广，采用模糊方法也可以更真实地建模。本文采用模糊数学规划和蜜蜂算法（BA）对2sALB问题进行建模和求解。salb问题是一个组合复问题。出于这个原因，BA被用作一种搜索机制，以获得良好的解决方案。BA是基于群智能的元启发式算法的一个相对较新的成员，它试图模仿真实蜜蜂在觅食中的自然行为来解决复杂的优化问题。文献中一般将BA应用于连续优化。它在组合问题上的应用很少。本文还首次将组合优化算法应用于组合优化中的装配线平衡问题。
Many real life problems contain imprecise variables, constraints and objectives. Fuzzy set theory gives an opportunity to handle imprecise terms in such situations. Two-sided assembly line balancing (2sALB) problem which is a generalization of the well known simple assembly line balancing problem can also be modeled more realistically by employing fuzzy approaches. Such an approach is presented in this study to model and solve 2sALB problem by employing fuzzy mathematical programming and Bees Algorithm (BA). 2sALB problem is a combinatorial complex problem. For this reason BA is employed as a search mechanism for obtaining good solutions to it. BA is a relatively new member of swarm intelligence based meta-heuristics that tries to mimic natural behavior of real honey bees in food foraging in solving complex optimization problems. BA is generally applied to continuous optimization in the literature. Its application to combinatorial problems is rare. This study also presents one of the first application of BA to an assembly line balancing problem which is member of combinatorial optimization.