Optimization of Multi-period Three-echelon Citrus Supply Chain Problem

In this paper, a new multi-objective integer non-linear programming model is developed for designing citrus three-echelon supply chain network. Short harvest period, product specifications, high perished rate, and special storing and distributing conditions make the modeling of citrus supply chain more complicated than other ones. The proposed model aims to minimize network costs including waste cost, transportation cost, and inventory holding cost, and to maximize network’s profits. To solve the model, firstly the model is converted to a linear programming model. Then three multi-objective meta-heuristic algorithms are used including MOPSO, MOICA, and NSGA-II for finding efficient solutions. The strengths and weaknesses of MOPSO, MOICA, and NSGA-II for solving the proposed model are discussed. The results of the algorithms have been compared by several criteria consisting of number of Pareto solution, maximum spread, mean ideal distance, and diversification metric.Computational results show that MOPSO algorithm finds competitive solutions in compare with NSGA-II and MOICA.

[1]  Behrouz Afshar-nadjafi,et al.  Using NSGA II and MOSA for solving multi-depots time-dependent vehicle routing problem with heterogeneous fleet , 2015 .

[2]  Lluis M. Plà-Aragonés,et al.  Handbook of operations research in agriculture and the agri-food industry , 2015 .

[3]  D. Hellström,et al.  Competence in supply chain management: a systematic review , 2017 .

[4]  Parviz Fattahi,et al.  A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers , 2016 .

[5]  Marjolein C. J. Caniëls,et al.  Exploring supply chain flexibility in a FMCG food supply chain , 2016 .

[6]  M. Pishvaee,et al.  Honey global supply chain network design using fuzzy optimization approach , 2017 .

[7]  Kannan Govindan,et al.  Two-echelon multiple-vehicle location-routing problem with time windows for optimization of sustainable supply chain network of perishable food , 2014 .

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

[9]  Behrouz Afshar-nadjafi,et al.  A Comparison of NSGA II and MOSA for Solving Multi-depots Time-dependent Vehicle Routing Problem with Heterogeneous Fleet , 2014 .

[10]  Francisco Saldanha-da-Gama,et al.  Facility location and supply chain management - A review , 2009, Eur. J. Oper. Res..

[11]  K. Govindan Sustainable consumption and production in the food supply chain: A conceptual framework , 2018 .

[12]  Caro Lucas,et al.  Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition , 2007, 2007 IEEE Congress on Evolutionary Computation.

[13]  Christine L. Mumford,et al.  A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling , 2014 .

[14]  Mauro Gamberi,et al.  Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization , 2016 .

[15]  Timothy J. Lowe,et al.  Decision Technologies for Agribusiness Problems: A Brief Review of Selected Literature and a Call for Research , 2004, Manuf. Serv. Oper. Manag..

[16]  Jason C. H. Chen,et al.  Location and allocation decisions for multi-echelon supply chain network - A multi-objective evolutionary approach , 2013, Expert Syst. Appl..

[17]  M. Osako,et al.  Food loss rate in food supply chain using material flow analysis. , 2017, Waste management.

[18]  Madjid Tavana,et al.  A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems , 2013, Reliab. Eng. Syst. Saf..

[19]  Bahman Naderi The Project Portfolio Selection and Scheduling Problem: Mathematical Model and Algorithms , 2013 .

[20]  Alireza Alinezhad,et al.  A multi-objective evolutionary approach for integrated production-distribution planning problem in a supply chain network , 2014 .

[21]  M. Eltoweissy,et al.  Issues and challenges , 2019, Justice for Children in the Context of Counter-Terrorism.

[22]  Maghsud Solimanpur,et al.  A new mathematical model for integrating all incidence matrices in multi-dimensional cellular manufacturing system , 2012 .

[23]  Yandra Arkeman,et al.  Multi-objective optimization for supply chain management problem: A literature review , 2016 .

[24]  M. H. Nehrir,et al.  Real-time energy management of an islanded microgrid using multi-objective Particle Swarm Optimization , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[25]  Marcela Cecilia González-Araya,et al.  Operational research models applied to the fresh fruit supply chain , 2016, Eur. J. Oper. Res..

[26]  F. Jolai,et al.  Solving a new multi-objective multi-route flexible flow line problem by multi-objective particle swarm optimization and NSGA-II , 2015 .

[27]  Ashkan Hafezalkotob,et al.  A Three-Echelon Multi-Objective Multi-Period Multi-Product Supply Chain Network Design Problem: A Goal Programming Approach , 2016 .

[28]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[29]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[30]  Navid Sahebjamnia,et al.  A particle swarm optimization for a fuzzy multi-objective unrelated parallel machines scheduling problem , 2013, Appl. Soft Comput..

[31]  Ardeshir Bahreininejad,et al.  A modified particle swarm optimization for solving the integrated location and inventory control problems in a two-echelon supply chain network , 2014, Journal of Intelligent Manufacturing.

[32]  Mir-Bahador Aryanezhad,et al.  A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty , 2011 .

[33]  Alireza Goli,et al.  A location-allocation model in the multi-level supply chain with multi-objective evolutionary approach , 2017 .

[34]  Saurav Negi,et al.  ISSUES AND CHALLENGES IN THE SUPPLY CHAIN OF FRUITS & VEGETABLES SECTOR IN INDIA: A REVIEW , 2015 .

[35]  Vahid Hajipour,et al.  A Continuous Review Inventory Control Model within the Batch Arrival Queuing Framework: A Parameter-Tuned Imperialist Competitive Algorithm , 2012 .

[36]  O. Ahumada,et al.  Operational model for planning the harvest and distribution of perishable agricultural products , 2011 .

[37]  Mahdi Heydari,et al.  A modified particle swarm optimization for disaster relief logistics under uncertain environment , 2012 .