The CAT metaheuristic for the solution of multi-period activity-based supply chain network design problems

This paper proposes an agent-based metaheuristic to solve large-scale multi-period supply chain network design problems. The generic design model formulated covers the entire supply chain, from vendor selection, to production–distribution sites configuration, transportation options and marketing policy choices. The model is based on the mapping of a conceptual supply chain activity graph on potential network locations. To solve this complex design problem, we propose Collaborative Agent Team (CAT), an efficient hybrid metaheuristic based on the concept of asynchronous agent teams (A-Teams). Computational results are presented and discussed for large-scale supply chain networks, and the results obtained with CAT are compared to those obtained with the latest version of CPLEX.

[1]  M. Balinski.  Fixed‐cost transportation problems , 1961 .

[2]  M. Goetschalckx,et al.  A primal decomposition method for the integrated design of multi-period production–distribution systems , 1999 .

[3]  M. Gen,et al.  Study on multi-stage logistic chain network: a spanning tree-based genetic algorithm approach , 2002 .

[4]  R. Ballou.  Business Logistics Management , 1991 .

[5]  David E. Peterson,et al.  A quantitative framework for financial management , 1969 .

[6]  Alok Aggarwal,et al.  Cooperative Multiobjective Decision Support for the Paper Industry , 1999, Interfaces.

[7]  Mitsuo Gen,et al.  The balanced allocation of customers to multiple distribution centers in the supply chain network: a genetic algorithm approach , 2002 .

[8]  Mehmet Ali Ilgin,et al.  Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art. , 2010, Journal of environmental management.

[9]  Alain Martel,et al.  Including technology selection decisions in manufacturing network design models , 2004, Int. J. Comput. Integr. Manuf..

[10]  M. Goetschalckx,et al.  MODELING THE EFFECT OF UNCERTAINTIES ON GLOBAL LOGISTICS SYSTEMS. , 2000 .

[11]  Eric Ballot,et al.  The reduction of greenhouse gas emissions from freight transport by pooling supply chains , 2013 .

[12]  H. Edwin Romeijn,et al.  Designing two-echelon supply networks , 2007, Eur. J. Oper. Res..

[13]  Gilbert Laporte,et al.  An iterated local search heuristic for the logistics network design problem with single assignment , 2008 .

[14]  Ali Amiri,et al.  Production , Manufacturing and Logistics Designing a distribution network in a supply chain system : Formulation and efficient solution procedure , 2005 .

[15]  Andreas Drexl,et al.  Facility location models for distribution system design , 2005, Eur. J. Oper. Res..

[16]  Turan Paksoy,et al.  A genetic algorithm approach for multi-objective optimization of supply chain networks , 2006, Comput. Ind. Eng..

[17]  Linus Schrage,et al.  OR Practice - A Scenario Approach to Capacity Planning , 1989, Oper. Res..

[18]  Alain Martel,et al.  Designing Multinational Value-Creating Supply Chain Networks for the Process Industry , 2010 .

[19]  Phuong Nga Thanh.  Conception et planification stratégique des réseaux logistiques complexes , 2008 .

[20]  Wilbert E. Wilhelm,et al.  Decomposition schemes and acceleration techniques in application to production-assembly-distribution system design , 2008, Comput. Oper. Res..

[21]  Daoud Ait-Kadi,et al.  A stochastic programming approach for designing supply loops , 2008 .

[22]  J. Shapiro.  Modeling the Supply Chain , 2000 .

[23]  Arthur M. Geoffrion,et al.  Twenty Years of Strategic Distribution System Design: An Evolutionary Perspective , 1995 .

[24]  Pierre Hansen,et al.  Primal-Dual Variable Neighborhood Search for the Simple Plant-Location Problem , 2003, INFORMS J. Comput..

[25]  R. John Milne,et al.  IBM Solves a Mixed-Integer Program to Optimize Its Semiconductor Supply Chain , 2006, Interfaces.

[26]  Marc Goetschalckx,et al.  A stochastic programming approach for supply chain network design under uncertainty , 2004, Eur. J. Oper. Res..

[27]  Mary J. Meixell,et al.  Global supply chain design: A literature review and critique , 2005 .

[28]  A. M. Geoffrion,et al.  Multicommodity Distribution System Design by Benders Decomposition , 1974 .

[29]  Panos M. Pardalos,et al.  Asynchronous Teams for probe selection problems , 2008, Discret. Optim..

[30]  Vaidyanathan Jayaraman,et al.  Production , Manufacturing and Logistics A simulated annealing methodology to distribution network design and management , 2002 .

[31]  Terry P. Harrison,et al.  Global Supply Chain Management at Digital Equipment Corporation , 1995 .

[32]  Andreas Klose,et al.  A Lagrangean relax-and-cut approach for the two-stage capacitated facility location problem , 2000, Eur. J. Oper. Res..

[33]  Marc Goetschalckx,et al.  A global supply chain model with transfer pricing and transportation cost allocation , 2001, Eur. J. Oper. Res..

[34]  Marielle Christiansen,et al.  Elkem Uses Optimization in Redesigning Its Supply Chain , 2006, Interfaces.

[35]  Kenneth Sörensen.  A framework for robust and flexible optimisation using metaheuristics , 2003, 4OR.

[36]  Alain Martel,et al.  A manufacturing network design model based on processor and worker capabilities , 2008 .

[37]  Bernhard Fleischmann,et al.  Strategic Planning of BMW's Global Production Network , 2006, Interfaces.

[38]  Rama Akkiraju,et al.  Asynchronous Teams , 2003, Handbook of Metaheuristics.

[39]  Marc Goetschalckx,et al.  Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms , 2002, Eur. J. Oper. Res..

[40]  A. Ramudhin,et al.  Design of sustainable supply chains under the emission trading scheme , 2012 .

[41]  Jean-François Cordeau,et al.  An integrated model for logistics network design , 2006, Ann. Oper. Res..

[42]  Matteo Fischetti,et al.  A feasibility pump heuristic for general mixed-integer problems , 2007, Discret. Optim..

[43]  Halit Üster,et al.  A closed-loop supply chain network design problem with integrated forward and reverse channel decisions , 2010 .

[44]  Mitsuo Gen,et al.  A steady-state genetic algorithm for multi-product supply chain network design , 2009, Comput. Ind. Eng..

[45]  Alain Martel,et al.  The design of robust value-creating supply chain networks , 2010, Eur. J. Oper. Res..

[46]  Robert Beauregard,et al.  Designing logistics networks in divergent process industries: A methodology and its application to the lumber industry , 2006 .

[47]  Ewa Ratajczak-Ropel.  Experimental Evaluation of the A-Team Solving Instances of the RCPSP/max Problem , 2010, KES-AMSTA.

[48]  John Rachlin,et al.  A-Teams: An Agent Architecture for Optimization and Decision Support , 1998, ATAL.

[49]  Timo Berthold,et al.  Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Improving the Feasibility Pump Improving the Feasibility Pump , 2022 .

[50]  Manish Bachlaus,et al.  Designing an integrated multi-echelon agile supply chain network: a hybrid taguchi-particle swarm optimization approach , 2008, J. Intell. Manuf..

[51]  Samir Elhedhli,et al.  Efficient Production-Distribution System Design , 2005, Manag. Sci..

[52]  Alain Martel,et al.  Network companies and competitiveness: A framework for analysis , 1999, Eur. J. Oper. Res..

[53]  V. Verter,et al.  An integrated evaluation of facility location, capacity acquisition, and technology selection for designing global manufacturing strategies , 1992 .

[54]  Alain Martel,et al.  A variable neighborhood search heuristic for the design of multicommodity production–distribution networks with alternative facility configurations , 2011, OR Spectr..

[55]  James R. Evans,et al.  Blending OR/MS, Judgment, and GIS: Restructuring P&G's Supply Chain , 1997 .

[56]  Mir Saman Pishvaee,et al.  A memetic algorithm for bi-objective integrated forward/reverse logistics network design , 2010, Comput. Oper. Res..

[57]  Mitsuo Gen,et al.  Integrated multistage logistics network design by using hybrid evolutionary algorithm , 2009, Comput. Ind. Eng..