scholarly journals Heuristics for the dynamic facility layout problem with unequal area departments

2008 ◽  
Author(s):  
◽  
Artak Hakobyan ◽  
Keyword(s):  
Material Handling ◽  
Facility Layout ◽  
Planning Horizon ◽  
Combinatorial Structure ◽  
Material Flows ◽  
Layout Problem ◽  
Dual Simplex Method ◽  
Data Set ◽  
Facility Layout Problem ◽  
Dual Simplex

The facility layout problem (FLP) is a well researched problem of finding positions of departments on a plant floor such that departments do not overlap and some objective(s) is (are) optimized. In this dissertation, the FLP with unequal area rectangular shaped departments is considered, when material flows between departments change during the planning horizon. This problem is known as the dynamic FLP. The change in material flows between pairs of departments in consecutive periods may require rearrangements of departments during the planning horizon in order to keep material handling costs low. The objective of our problem is to minimize the sum of the material handling and rearrangement costs. Because of the combinatorial structure of the problem, only small sized problems can be solved in reasonable time using exact techniques. As a result, construction and improvement heuristics are developed for the proposed problem. The construction algorithms are boundary search heuristics as well as a dual simplex method, and the improvement heuristics are tabu search and memetic heuristics with boundary search and dual simplex (linear programming model) techniques. The heuristics were tested on a generated data set as well as some instances from the literature. In summary, the memetic heuristic with the boundary search technique out-performed the other techniques with respect to solution quality.

scholarly journals A new soft computing algorithm based on cloud theory for dynamic facility layout problem

2020 ◽  
Author(s):  
Mostafa Zandieh ◽  
Seyed Shamsodin Hosseini ◽  
parham azimi ◽  
Mani Sharifi
Keyword(s):  
Material Handling ◽  
Simulated Annealing Algorithm ◽  
Facility Layout ◽  
Planning Horizon ◽  
Test Problems ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Dynamic Facility Layout Problem ◽  
Material Handling Costs ◽  
Cloud Theory

This paper deals with dynamic facility layout problem (DFLP) in a plant which is concerned with determining the best position of machines in the plant during a multi-period planning horizon. The material handling costs and machines rearrangement costs are used to determine the best layout. In addition to positions of machines, the details of transportation such as type of transporters and sequence of transportation operations have a direct effect on MHC. Therefore, it is more realistic to consider the transportation details during DFLP optimization. This paper proposes a new mathematical model to simultaneously determine the best position of machines in each period and to plan the transportation operations. Minimizing sum of MHC and MRC is considered as the objective function. A new hybrid meta-heuristic approach has been developed by combining modified genetic algorithm and cloud-based simulated annealing algorithm to solve the model. Finally, the proposed methodology is compared with two meta-heuristics on a set of test problems.

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.

Optimisation of Facility Layout Problem at Automotive Industry a Case Study in Sabah

2013 ◽  
Vol 315 ◽  
pp. 755-761 ◽  
Author(s):  
Kah Song Tan ◽  
Noor Ajian Mohd-Lair ◽  
Stephen Yong Nai-Vun ◽  
James Yong Chau-Leong
Keyword(s):  
Material Handling ◽  
Facility Layout ◽  
Production Capacity ◽  
Layout Problem ◽  
Throughput Time ◽  
Facility Layout Problem ◽  
Manufacturing Line ◽  
Handling Cost ◽  
Material Handling Cost ◽  
Arena Simulation

The general Facility Layout Problem deals with the arrangement of machines within the facility based on the constraints such as material flow distance, volume of flow of products, material handling cost and operation sequence of product. The facility layout problem is directly linked with the efficiency of the facility or the manufacturing line. The objective of this project is to design a simulation based methodology experiment on designing an optimized facility layout and evaluating the proposed alternative layouts using ARENA simulation. This project is conducted at Benteng Motor Sdn. Bhd. in Kota Kinabalu, Sabah. Currently, the company is planning to expand their manufacturing plant and hence the company needs an optimized facility layout to maximize the product capacity and manufacturing throughput time on a minimum utilization of resources environment. An eight steps simulation methodology is being proposed to design an optimized facility layout. A manufacturing re-engineering scenario has been developed to improve the existing system. The proposed scenario was evaluated using Arena simulation student package. The scenario has significantly increases the production capacity up to 225%, decrease the manufacturing throughput time by 19% as well as increase the utilization of majority of the manufacturing resources more than 200%.

Improved Bi-Level Mathematical Programming and Heuristics for the Cellular Manufacturing Facility Layout Problem

2015 ◽  
Author(s):  
Maral Zafar Allahyari ◽  
Ahmed Azab
Keyword(s):  
Material Handling ◽  
Metal Cutting ◽  
Cellular Manufacturing ◽  
Facility Layout ◽  
Setup Time ◽  
Continuous Model ◽  
Mixed Integer ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Work In Process

A good layout plan results in improvements in machine utilization, setup time, and reduction in work-in-process inventory and material handling cost. Facility layout problem (FLP) for CMS includes both intercellular- and intracellular-layout. Most of the literature takes a discrete approach and rarely considers operations sequence and part demand. In this paper, a novel bi-level heuristic and mixed-integer non-linear programming continuous model for the layout design of cellular manufacturing are developed. Machine tools and manufacturing cells layout are determined sequentially by solving a leader and follower problem, respectively. Facilities are assumed unequal sizes. Both overlap elimination and aisle constraint modeling have been considered. The model is nonlinear; problem is NP-hard. Hence, only small instances of the problem can be solved using the exact linearized model. The developed heuristic is used to solve large instances of the problem. A real case study from the metal cutting inserts industry, where multiple families of inserts have been formed, each with its distinguished master plan, is presented.

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