A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
An ant algorithm for the single row layout problem in flexible manufacturing systems
Computers and Operations Research
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing)
A new lower bound for the single row facility layout problem
Discrete Applied Mathematics
Expert Systems with Applications: An International Journal
A particle swarm optimization for the single row facility layout problem
Computers and Industrial Engineering
Extended artificial chromosomes genetic algorithm for permutation flowshop scheduling problems
Computers and Industrial Engineering
On the convergence of a class of estimation of distribution algorithms
IEEE Transactions on Evolutionary Computation
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The layout positioning problem of facilities on a straight line is known as Single Row Facility Layout Problem (SRFLP). The objective of SRFLP, categorized as NP Complete problem, is to arrange the layout so that the sum of distances between all facilities' pairs can be minimized. Estimation of Distribution Algorithm (EDA) efficiently improves the solution quality in first few runs, but the diversity loss grows rapidly as more iterations are run. To maintain the diversity, hybridization with metaheuristic algorithms is needed. This research proposes Hybrid Estimation of Distribution Algorithm (EDAhybrid), an algorithm which consists of hybridization of EDA, Particle Swarm Optimization (PSO), and Tabu Search. Another hybridization algorithm, extended Artificial Chromosomes Genetic Algorithm (eACGA), is also built as benchmark. EDAhybrid's performance is tested in 15 benchmark problems of SRFLP and it successfully achieves optimum solution. Moreover, the mean error rates of EDAhybrid always get the lowest value compared to other algorithms. SRFLP can be enhanced by considering more constraints, so it becomes enhanced SRFLP. Computational results show that EDAhybrid can also solve Enhanced SRFLP effectively. Therefore, we can conclude that EDAhybrid is a promising metaheuristic algorithm which can be used to solve the basic and enhanced SRFLP.