scholarly journals AN INTEGRATED APPROACH BASED ON A BI-LEVEL GENETIC ALGORITHM AND A COMBINED ZONE- LP FOR THE FACILITY LAYOUT PROBLEM

2019 ◽  
Vol 30 (4) ◽  
Author(s):  
Arash Mohamadi ◽  
Sadalah Ebrahimnejad ◽  
Roya Soltani ◽  
Mohammad Khalilzadeh
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Integrated Approach ◽  
Layout Problem ◽  
Facility Layout Problem

Single row facility layout problem using a permutation-based genetic algorithm

2011 ◽  
Vol 213 (2) ◽  
pp. 388-394 ◽  
Author(s):  
Dilip Datta ◽  
André R.S. Amaral ◽  
José Rui Figueira
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Single Row

scholarly journals Genetic algorithm using a modified backward pass heuristic for the dynamic facility layout problem *

2011 ◽  
Vol 2 (3) ◽  
Author(s):  
Kazi Shah Nawaz Ripon ◽  
Kyrre Glette ◽  
Dirk Koch ◽  
Mats Hovin ◽  
Jim Torresen
Keyword(s):  
Genetic Algorithm ◽  
Material Handling ◽  
Manufacturing System ◽  
Industrial Robot ◽  
Facility Layout ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Dynamic Facility Layout Problem ◽  
Economical Consideration ◽  
Over Time

AbstractLayout planning in a manufacturing company is an important economical consideration. In the past, research examining the facility layout problem (FLP) generally concerned static cases, where the material flows between facilities in the layout have been assumed to be invariant over time. However, in today’s real-world scenario, manufacturing system must operate in a dynamic and market-driven environment in which production rates and product mixes are continuously adapting. The dynamic facility layout problem (DFLP) addresses situations in which the flow among various facilities changes over time. Recently, there is an increasing trend towards implementation of industrial robot as a material handling device among the facilities. Reducing the robot energy usage for transporting materials among the facilities of an optimal layout for completing a product will result in an increased life for the robots and thus enhance the productivity of the manufacturing system. In this paper, we present a hybrid genetic algorithm incorporating jumping genes operations and a modified backward pass pair-wise exchange heuristic to determine its effectiveness in optimizing material handling cost while solving the DFLP. A computational study is performed with several existing heuristic algorithms. The experimental results show that the proposed algorithm is effective in dealing with the DFLP.

Research on Manufacturing Engineering with Facility Layout’s Modeling and Simulation Based on Genetic Algorithm

2014 ◽  
Vol 910 ◽  
pp. 385-388
Author(s):  
Jun Lu ◽  
Peng Dan Dai
Keyword(s):  
Genetic Algorithm ◽  
Modeling And Simulation ◽  
Production Cost ◽  
Facility Layout ◽  
Great Influence ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Simulation Based ◽  
Manufacturing Engineering

The facility layout problem has great influence on the production cost and manufacturing engineering.This paper puts forward a method to solve the facility layout problem based on Genetic Algorithm,using eM-plant to build the model and to carry on the analysis.At last, it uses an example to verify this method’s feasibility.

scholarly journals A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search

2019 ◽  
Vol 31 (3) ◽  
pp. 615-640 ◽  
Author(s):  
Mariem Besbes ◽  
Marc Zolghadri ◽  
Roberta Costa Affonso ◽  
Faouzi Masmoudi ◽  
Mohamed Haddar
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Layout Problem ◽  
Facility Layout Problem

scholarly journals On GPU Implementation of the Island Model Genetic Algorithm for Solving the Unequal Area Facility Layout Problem

2018 ◽  
Vol 8 (9) ◽  
pp. 1604 ◽  
Author(s):  
Xue Sun ◽  
Lien-Fu Lai ◽  
Ping Chou ◽  
Liang-Rui Chen ◽  
Chao-Chin Wu
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Optimal Solution ◽  
Industrial Engineering ◽  
Island Model ◽  
Time Interval ◽  
Efficient Production ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Gpu Implementation

Facility layout problem (FLP) is one of the hottest research areas in industrial engineering. A good facility layout can achieve efficient production management, improve production efficiency, and create high economic values. Because FLP is an NP-hard problem, meaning it is impossible to find the optimal solution when problem becomes sufficiently large, various evolutionary algorithms (EAs) have been proposed to find a sub-optimal solution within a reasonable time interval. Recently, a genetic algorithm (GA) was proposed for unequal area FLP (UA-FLP), where the areas of facilities are not identical. More precisely, the GA is an island model based, which is called IMGA. Since EAs are still very time consuming, many efforts have been devoted to how to parallelize various EAs including IMGA. In recent work, Steffen and Dietmar proposed how to parallelize island models of EAs. However, their parallelization approaches are preliminary because they focused mainly on comparing the performances between different parallel architectures. In addition, they used one mathematical function to model the problem. To further investigate on how to parallelize the IMGA by GPU, in this paper we propose multiple parallel algorithms, for each individual step in the IMGA when solving the industrial engineering problem, UA-FLP, and conduct experiments to compare their performances. After integrating better algorithms for all steps into the IMGA, our GPU implementation outperforms the CPU counterpart and the best speedup can be as high as 84.

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