scholarly journals A New Optimization via Simulation Approach for Dynamic Facility Layout Problem with Budget Constraints

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Parham Azimi ◽  
Hamid Reza Charmchi
Keyword(s):  
Integer Programming ◽  
Simulation Model ◽  
Heuristic Algorithms ◽  
Facility Layout ◽  
Discrete Event ◽  
Test Problems ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Dynamic Facility Layout Problem ◽  
Optimization Via Simulation

A new efficient heuristic algorithm has been developed for the dynamic facility layout problem with budget constraint (DFLPB) using optimization via simulation technique. The heuristic integrates integer programming and discrete event simulation to address DFLPB. In the proposed algorithm, the nonlinear model of the DFLP has been changed to a pure integer programming (PIP) model. Then, the optimal solution of the PIP model has been used in a simulation model that has been designed in a similar manner as the DFLP for determining the probability of assigning a facility to a location. After a sufficient number of runs, the simulation model obtains near optimum solutions. Finally, to test the performance of the algorithm, several test problems have been taken from the literature and solved. The results show that the proposed algorithm is more efficient in terms of speed and accuracy than other heuristic algorithms presented in previous works.

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.

DYNAMIC FACILITY LAYOUT WITH MULTI-OBJECTIVES

2014 ◽  
Vol 31 (04) ◽  
pp. 1450027 ◽  
Author(s):  
GARY YU-HSIN CHEN ◽  
JU-CHIEH LO
Keyword(s):  
Quadratic Assignment Problem ◽  
Facility Layout ◽  
Quadratic Assignment ◽  
Data Sets ◽  
Multiple Time ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Dynamic Facility Layout Problem ◽  
Multi Objective

A problem in multi-objective dynamic facility layout is achieving distance- and adjacency-based objectives for arranging facility layouts across multiple time periods. As a non-deterministic polynomial time-hard problem, it resembles the quadratic assignment problem (QAP), which can be solved through meta-heuristics such as ant colony optimization (ACO). This study investigates three multi-objective approaches coupled with ACO to solve this problem. As the experimental design, we apply the proposed methods to solve the dynamic facility layout problem (DFLP), multi-objective facility layout problem, and multi-objective DFLP based on data sets from the literature to test the quality of the solution. The results show that the proposed methods are effective for solving the problem.

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