A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic Algorithm or modified Backtracking Search Algorithm

Abstract Facility layout problems (FLP) involve determining the optimal placement of machines within a fixed space. An effective layout minimises costs. The total material travel distance is a key indicator of the efficiency of internal logistics. Changes in demand and product mix may alter the material flow. The dynamic facilities layout problem (DFLP) takes into account changes in demand and allows for the periodic redesign of facilities. Facility redesign may reduce the material flow cost, but there is a trade-off between material flow improvements and reorganisation costs. There is a limited literature on the redesign of facilities with stochastic demand, heterogeneous-sized resources and rectilinear material flow. The Backtracking Search Algorithm (BSA) has been used to successfully solve a range of engineering problems, but it has not previously been used to solve operations management problems or the FLP. This paper outlines novel modified Backtracking Search Algorithms (mBSAs) that solved the stochastic DFLP with heterogeneous sized resources. The combination of material flow and redesign costs were minimised. Three mBSA were benchmarked against the classical BSA and a Genetic Algorithm (GA) using 11 benchmark datasets obtained from the literature. The best mBSA generated better solutions than the GA for large-size problems. The total costs for the layouts generated by the best mBSA were significantly lower than for the conventional BSA. The modifications to the BSA increased the diversity of candidate solutions, which increased the amount of exploration. The computational time required by the three mBSAs was up to 70% less than the GA.

[1]  Suresh P. Sethi,et al.  Flexibility in manufacturing: A survey , 1990 .

[2]  Panos M. Pardalos,et al.  Simulated Annealing and Genetic Algorithms for the Facility Layout Problem: A Survey , 1997, Comput. Optim. Appl..

[3]  Haibin Duan,et al.  Backtracking search algorithm for non-aligned thrust optimization for satellite formation , 2014, 11th IEEE International Conference on Control & Automation (ICCA).

[4]  Long Wen,et al.  A hybrid backtracking search algorithm for permutation flow-shop scheduling problem minimizing makespan and energy consumption , 2017 .

[5]  Haibin Duan,et al.  Adaptive Backtracking Search Algorithm for Induction Magnetometer Optimization , 2014, IEEE Transactions on Magnetics.

[6]  Alireza Askarzadeh,et al.  Parameter estimation of fuel cell polarization curve using BMO algorithm , 2013 .

[7]  Charles R. Standridge,et al.  Modeling and Analysis of Manufacturing Systems , 1993 .

[8]  Riccardo Poli,et al.  Particle Swarm Optimisation , 2011 .

[9]  Pupong Pongcharoen,et al.  Identifying Optimum Parameter Setting for Layout Design via Experimental Design and Analysis , 2014 .

[10]  B. Montreuil,et al.  Dynamic layout design given a scenario tree of probable futures , 1992 .

[11]  Jing J. Liang,et al.  Comprehensive learning particle swarm optimizer for global optimization of multimodal functions , 2006, IEEE Transactions on Evolutionary Computation.

[12]  Alan R. McKendall,et al.  Simulated annealing heuristics for the dynamic facility layout problem , 2006, Comput. Oper. Res..

[13]  Xueqiang Zhang,et al.  Backtracking search algorithm for effective and efficient surface wave analysis , 2015 .

[14]  Pupong Pongcharoen,et al.  The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure , 2004, Eur. J. Oper. Res..

[15]  S. Sooncharoen.  Application of Biogeography-Based Optimisation for Machine Layout Design Problem , 2015 .

[16]  Bashar Zogheib.  Elementary Statistics: A Step by Step Approach , 2012 .

[17]  Pupong Pongcharoen,et al.  The Backtracking Search Algorithm for designing a robust machine layout , 2014 .

[18]  P. N. Suganthan,et al.  Problem Definitions and Evaluation Criteria for CEC 2011 Competition on Testing Evolutionary Algorithms on Real World Optimization Problems , 2011 .

[19]  M. Adel El-Baz,et al.  A genetic algorithm for facility layout problems of different manufacturing environments , 2004, Comput. Ind. Eng..

[20]  Chien-Wei Wu,et al.  An efficient approach to determine cell formation, cell layout and intracellular machine sequence in cellular manufacturing systems , 2013, Comput. Ind. Eng..

[21]  Yeong-Dae Kim,et al.  Algorithms for adjusting shapes of departments in block layouts on the grid-based plane , 2000 .

[22]  Mostafa Abedzadeh,et al.  Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm , 2013 .

[23]  Yavuz A. Bozer,et al.  A reexamination of the distance-based facility layout problem , 1997 .

[24]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[25]  Henri Pierreval,et al.  Facility layout problems: A survey , 2007, Annu. Rev. Control..

[26]  Mitsuo Gen,et al.  Network Models and Optimization: Multiobjective Genetic Algorithm Approach , 2008 .

[27]  Mario Enea,et al.  The facility layout problem approached using a fuzzy model and a genetic search , 2005, J. Intell. Manuf..

[28]  Christian Hicks,et al.  A genetic algorithm tool for designing manufacturing facilities in the capital goods industry , 2004 .

[29]  Stefan Roth,et al.  Covariance Matrix Adaptation for Multi-objective Optimization , 2007, Evolutionary Computation.

[30]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[31]  Mitsuo Gen,et al.  Genetic algorithms and engineering design , 1997 .

[32]  Christian Hicks,et al.  A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry , 2006 .

[33]  Ulaş Kılıç,et al.  Backtracking search algorithm-based optimal power flow with valve point effect and prohibited zones , 2014, Electrical Engineering.

[34]  Pupong Pongcharoen,et al.  A tool for generating optimum facilities layouts under demand uncertainty with/without machine breakdown , 2014 .

[35]  Haitao Liao,et al.  Mitigation of risk in facility layout design for single and multi-period problems , 2009 .

[36]  Su-Jin Lee,et al.  Equivalent Circuit Considering the Harmonics of Core Loss in the Squirrel-Cage Induction Motor for Electrical Power Steering Application , 2014, IEEE Transactions on Magnetics.

[37]  Leandro dos Santos Coelho,et al.  A backtracking search algorithm combined with Burger's chaotic map for parameter estimation of PEMFC electrochemical model , 2014 .

[38]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[39]  Erhan Kozan,et al.  Ant Colony Optimisation for Machine Layout Problems , 2004, Comput. Optim. Appl..

[40]  Orhan Türkbey,et al.  A new hybrid tabu-simulated annealing heuristic for the dynamic facility layout problem , 2009 .

[41]  A. Nagar,et al.  Multiple and bicriteria scheduling : A literature survey , 1995 .

[42]  Uday K. Chakraborty,et al.  PEM fuel cell modeling using differential evolution , 2012 .

[43]  Haldun Aytug,et al.  Use of genetic algorithms to solve production and operations management problems: A review , 2003 .

[44]  Thatchai Thepphakorn,et al.  An ant colony based timetabling tool , 2014 .

[45]  Wenyin Gong,et al.  Accelerating parameter identification of proton exchange membrane fuel cell model with ranking-based differential evolution , 2013 .

[46]  Krishna K. Krishnan,et al.  Design of robust layout for Dynamic Plant Layout Problems , 2011, Comput. Ind. Eng..

[47]  Pupong Pongcharoen,et al.  Best-Worst Ant Colony System Parameter Investigation by Using Experimental Design and Analysis for Course Timetabling Problem , 2010, 2010 Second International Conference on Computer and Network Technology.

[48]  Mohammad Mahdi Paydar,et al.  A Simulated Annealing for Intra-Cell Layout Design of Dynamic Cellular manufacturing Systems with Route Selection, purchasing Machines and Cell Reconfiguration , 2013, Asia Pac. J. Oper. Res..

[49]  S. Ghoshal,et al.  Interference suppression of linear antenna arrays with combined Backtracking Search Algorithm and Differential Evolution , 2014, 2014 International Conference on Communication and Signal Processing.

[50]  Pupong Pongcharoen,et al.  Bat Algorithm, Genetic Algorithm and Shuffled Frog Leaping Algorithm for Designing Machine Layout , 2013, MIWAI.

[51]  Nadia Nedjah,et al.  Distributed Efficient Node Localization in Wireless Sensor Networks Using the Backtracking Search Algorithm , 2014, ICA3PP.

[52]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[53]  A. Rezaee Jordehi,et al.  Brainstorm optimisation algorithm (BSOA): An efficient algorithm for finding optimal location and setting of FACTS devices in electric power systems , 2015 .

[54]  John Wang,et al.  Facility layout optimization using simulation and genetic algorithms , 2000 .

[55]  Da Ruan,et al.  Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems , 2006, Inf. Sci..

[56]  Pupong Pongcharoen,et al.  Modifying Particle Swarm Optimisation and Genetic Algorithm for Solving Multiple Container Packing Problems , 2009, 2009 International Conference on Computer and Automation Engineering.

[57]  A. Kai Qin,et al.  Self-adaptive differential evolution algorithm for numerical optimization , 2005, 2005 IEEE Congress on Evolutionary Computation.

[58]  Günter Radons,et al.  Combining evolutionary computation and dynamic programming for solving a dynamic facility layout problem , 2005, Eur. J. Oper. Res..

[59]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[60]  S. Hossein Cheraghi,et al.  Facility layout design for multiple production scenarios in a dynamic environment , 2008 .

[61]  Krishna K. Krishnan,et al.  A simulation-based approach for risk assessment of facility layout designs under stochastic product demands , 2010 .

[62]  Nasrudin Abd Rahim,et al.  Solving non-convex economic dispatch problem via backtracking search algorithm , 2014 .

[63]  T. S. Lee,et al.  Intelligent design of a dynamic machine layout in uncertain environment of flexible manufacturing systems , 2012, J. Intell. Manuf..

[64]  S. S. Chaudhry *,et al.  Application of genetic algorithms in production and operations management: a review , 2005 .

[65]  Pinar Çivicioglu,et al.  Backtracking Search Optimization Algorithm for numerical optimization problems , 2013, Appl. Math. Comput..

[66]  Reza Tavakkoli-Moghaddam,et al.  Design of a facility layout problem in cellular manufacturing systems with stochastic demands , 2007, Appl. Math. Comput..

[67]  P. Pongcharoena,et al.  Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products , 2002 .

[68]  Wai Kin Chan,et al.  A Monte Carlo simulation based heuristic procedure for solving dynamic line layout problems for facilities using conventional material handling devices , 2010 .

[69]  Türkay Dereli,et al.  An ant colony algorithm for solving budget constrained and unconstrained dynamic facility layout problems , 2006 .

[70]  Hani Pourvaziri,et al.  A hybrid multi-population genetic algorithm for the dynamic facility layout problem , 2014, Appl. Soft Comput..

[71]  Yilong Yin,et al.  An Improved Backtracking Search Algorithm for Constrained Optimization Problems , 2014, KSEM.

[72]  K. Y. Tam,et al.  Genetic algorithms, function optimization, and facility layout design , 1992 .

[73]  Taho Yang,et al.  Flexible machine layout design for dynamic and uncertain production environments , 1998, Eur. J. Oper. Res..

[74]  Pupong Pongcharoen,et al.  Improving Artificial Immune System Performance: Inductive Bias and Alternative Mutations , 2008, ICARIS.

[75]  Gary Yu-Hsin Chen.  A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems , 2013 .

[76]  Tapio Westerlund,et al.  Optimization of block layout design problems with unequal areas: A comparison of MILP and MINLP optimization methods , 2005, Comput. Chem. Eng..