A parallel tabu search for solving the primal buffer allocation problem in serial production systems

This paper presents a novel parallel tabu search (PTS) algorithm equipped with a proper adaptive neighborhood generation mechanism to solve the primal buffer allocation problem, which consists of minimizing the total buffer capacity of a serial production system under a minimum throughput rate constraint. An evaluative method based on a specific algorithm has been implemented to simulate the system behavior. In order to validate the effectiveness of the proposed PTS a mixed integer linear programming-based simulation/optimization approach and several metaheuristics from the relevant literature have been implemented. Since most metaheuristics are sensitive to the parameter setting, a proper calibration analysis based on a non-parametric test has been performed. Then, a comprehensive comparison analysis, concerning with both quality of solutions and computational efficiency, has been carried out. Finally, through the numerical results obtained from PTS, a multi-factorial experimental analysis has been developed to analyze the influencing factors of the problem under investigation. We study the buffer allocation problem under a minimum throughput rate.We develop a tabu search inspired to the parallel computing applications.We compare the proposed approach with other metaheuristic techniques.A non-parametric test emphasizes the effectiveness of the proposed approach.

[1]  Mustapha Nourelfath,et al.  A new approach for buffer allocation in unreliable production lines , 2006 .

[2]  H. T. Papadopoulos,et al.  A heuristic algorithm for the buffer allocation in unreliable unbalanced production lines , 2001 .

[3]  H. B. Mann,et al.  On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other , 1947 .

[4]  El-Ghazali Talbi,et al.  Metaheuristics - From Design to Implementation , 2009 .

[5]  Chrissoleon T. Papadopoulos,et al.  A dynamic programming algorithm for the buffer allocation problem in homogeneous asymptotically reliable serial production lines , 2004 .

[6]  M. Senthil Arumugam,et al.  A new and improved version of particle swarm optimization algorithm with global–local best parameters , 2008, Knowledge and Information Systems.

[7]  Yushin Hong,et al.  Heuristic algorithms for buffer allocation in a production line with unreliable machines , 1995 .

[8]  Gerrit K. Janssens,et al.  A Petri net model of a continuous flow transfer line with unreliable machines , 2004, Eur. J. Oper. Res..

[9]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[10]  Ihsan Sabuncuoglu,et al.  Analysis of serial production lines: characterisation study and a new heuristic procedure for optimal buffer allocation , 2006 .

[11]  James R. Wilson,et al.  Optimal buffer inventories for multistage production systems with failures , 1991 .

[12]  Lionel Amodeo,et al.  Efficient combined immune-decomposition algorithm for optimal buffer allocation in production lines for throughput and profit maximization , 2010, Comput. Oper. Res..

[13]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[14]  Dan R. Staley,et al.  Experimental results for the allocation of buffers in closed serial production lines , 2012 .

[15]  Sooyoung Kim,et al.  Allocation of buffer capacity to minimize average work-in-process , 2001 .

[16]  Minghe Sun,et al.  Determining buffer location and size in production lines using tabu search , 1998, Eur. J. Oper. Res..

[17]  Yu Song,et al.  Optimization of buffer-size allocation using dynamic programming in assembly-like systems , 2010 .

[18]  Stanley B. Gershwin,et al.  Manufacturing Systems Engineering , 1993 .

[19]  Gunar E. Liepins,et al.  Some Guidelines for Genetic Algorithms with Penalty Functions , 1989, ICGA.

[20]  Yeong-Dae Kim,et al.  Algorithms for determining capacities of individual buffers in assembly/disassembly systems , 1997 .

[21]  Kelvin C. W. So,et al.  The effect of the coefficient of variation of operation times on the allocation of storage space in , 1991 .

[22]  Ying-Chyi Chou,et al.  Buffer allocation in flow-shop-type production systems with general arrival and service patterns , 2002, Comput. Oper. Res..

[23]  F. Cruz,et al.  The buffer allocation problem for general finite buffer queueing networks , 2005 .

[24]  P. N. Suganthan,et al.  Differential Evolution: A Survey of the State-of-the-Art , 2011, IEEE Transactions on Evolutionary Computation.

[25]  Stanley B. Gershwin,et al.  Efficient algorithms for buffer space allocation , 2000, Ann. Oper. Res..

[26]  Zbigniew Michalewicz,et al.  Genetic Algorithms Plus Data Structures Equals Evolution Programs , 1994 .

[27]  Anton V. Eremeev,et al.  HBBA: hybrid algorithm for buffer allocation in tandem production lines , 2007, J. Intell. Manuf..

[28]  Dirk P. Kroese,et al.  Application of the Cross-Entropy Method to the Buffer Allocation Problem in a Simulation-Based Environment , 2005, Ann. Oper. Res..

[29]  C. T. Papadopoulos,et al.  An artificial neural network based decision support system for solving the buffer allocation problem in reliable production lines , 2013, Comput. Ind. Eng..

[30]  Anton V. Eremeev,et al.  A Genetic Algorithm for the Allocation of Buffer Storage Capacities in a Production Line with Unreliable Machines , 2002, J. Math. Model. Algorithms.

[31]  Chrissoleon T. Papadopoulos,et al.  A DSS for the buffer allocation of production lines based on a comparative evaluation of a set of search algorithms , 2013 .

[32]  Kusum Deep,et al.  A real coded genetic algorithm for solving integer and mixed integer optimization problems , 2009, Appl. Math. Comput..

[33]  Kusum Deep,et al.  A new crossover operator for real coded genetic algorithms , 2007, Appl. Math. Comput..

[34]  Gregory W. Corder,et al.  Nonparametric Statistics : A Step-by-Step Approach , 2014 .

[35]  We-Min Chow,et al.  Buffer capacity analysis for sequential production lines with variable process times , 1987 .

[36]  Leyuan Shi,et al.  Optimal buffer allocation in production lines , 2003 .

[37]  Yves Dallery,et al.  Manufacturing flow line systems: a review of models and analytical results , 1992, Queueing Syst. Theory Appl..

[38]  C. Reeves.  Modern heuristic techniques for combinatorial problems , 1993 .

[39]  Eugeniusz Nowicki,et al.  The flow shop with parallel machines: A tabu search approach , 1998, Eur. J. Oper. Res..

[40]  F. Cruz,et al.  Buffer allocation in general single-server queueing networks , 2008, Comput. Oper. Res..

[41]  B. Atkinson.  Queuing Theory in Manufacturing Systems Analysis and Design , 1995 .

[42]  John A. Buzacott,et al.  Stochastic models of manufacturing systems , 1993 .

[43]  Carlos A. Coello Coello,et al.  Constraint-handling in genetic algorithms through the use of dominance-based tournament selection , 2002, Adv. Eng. Informatics.

[44]  Diomidis Spinellis,et al.  Analysis and Design of Discrete Part Production Lines , 2009, Optimization and its applications.

[45]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[46]  Vicente Martinez Delgado.  The buffer allocation problem for general finite buffer queuing networks: A survey , 2015 .

[47]  Hsu-Tung Lee,et al.  A Meta-heuristic Approach to Buffer Allocation in Production Line , 2009 .

[48]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[49]  Deniz Türsel Eliiyi,et al.  The state of the art on buffer allocation problem: a comprehensive survey , 2014, J. Intell. Manuf..

[50]  Deniz Türsel Eliiyi,et al.  An adaptive tabu search approach for buffer allocation problem in unreliable non-homogenous production lines , 2012, Comput. Oper. Res..

[51]  Diomidis Spinellis,et al.  Stochastic Algorithms for Buffer Allocation in Reliable Production Lines , 2000 .

[52]  S. Gershwin,et al.  A segmentation approach for solving buffer allocation problems in large production systems , 2016 .

[53]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[54]  Frederick S. Hillier,et al.  The effect of machine breakdowns and interstage storage on the performance of production line systems , 1991 .

[55]  Andrea Matta,et al.  Simulation optimization with mathematical programming representation of discrete event systems , 2008, 2008 Winter Simulation Conference.

[56]  Arne Løkketangen,et al.  Two approaches for solving the buffer allocation problem in unreliable production lines , 2013, Comput. Oper. Res..

[57]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.