Towards mathematical modeling for selecting logistics service providers: case of moroccan LSP
محورهای موضوعی :
Jabir Arif
1
,
Khaoula Azzouz
2
,
Mohamed Badr Benboubker
3
1 - Sidi Mohamed Ben Abdellah University
2 - Mathematics , National School of Applied Sciences, Abdemalek Essaadi University, Tetouan,Morocco
3 - Mathematics, National School of Applied Sciences of Tetouan, Abdelmalek Essaadi University, Tetouan.Morocco
کلید واژه: linear programming, Linear model, Contractors, Decision Making Methods, Mathematical modeling approach,
چکیده مقاله :
With the global market's growing competition, the use of logistics services in Morocco has become an urgent necessity to optimize costs and improve service quality.To succeed in this strategy, guidelines are proposed for the accompaniment of contractors. One of the fundamental pillars of this strategy is based on the choice of an efficient partner, which we call a Logistics Services Provider (LSP).Indeed, the bibliography contains numerous decision-making methods, so decision-makers have faced the challenge of selecting the most relevant method.The main challenge is to always seek the effectiveness and sustainability of the relationship in a network of potential partners, often very complex. To this purpose, an eminent need to model this relationship linking the actors of this network is required.The study carried out involves modeling the problem of LSP selection and the assignment of the service to be outsourced to the appropriate LSP. The linear model developed takes into account both qualitative and quantitative criteria. The model developed aims to optimize the overall cost of selecting the suitable LSP.The resolution method chosen for this problem is the Branch and Bound method and the tool used for the coding of this linear program is CPLEX.
With the global market's growing competition, the use of logistics services in Morocco has become an urgent necessity to optimize costs and improve service quality.To succeed in this strategy, guidelines are proposed for the accompaniment of contractors. One of the fundamental pillars of this strategy is based on the choice of an efficient partner, which we call a Logistics Services Provider (LSP).Indeed, the bibliography contains numerous decision-making methods, so decision-makers have faced the challenge of selecting the most relevant method.The main challenge is to always seek the effectiveness and sustainability of the relationship in a network of potential partners, often very complex. To this purpose, an eminent need to model this relationship linking the actors of this network is required.The study carried out involves modeling the problem of LSP selection and the assignment of the service to be outsourced to the appropriate LSP. The linear model developed takes into account both qualitative and quantitative criteria. The model developed aims to optimize the overall cost of selecting the suitable LSP.The resolution method chosen for this problem is the Branch and Bound method and the tool used for the coding of this linear program is CPLEX.
Aboudrar, L., El Baz, J. & Batrich, H. (2014). Impact de l’externalisation du transport/logistique sur le triptyque coût-qualite-délai : cas des entreprises marocaines, Dossiers de Recherches en Economie et Gestion : Numéro spécial, pp464-484, Décembre
Ahmadi, R.H. & Tang, C.S. (1994). Production allocation whith dual provising, European Journal Of Operational Research, 75(1), 186-199, doi.org/10.1016/0377-2217(94)90193-7
Akgün, M. & Gürünlü, M. (2010). Cash to cash cycle as an integral performance metric in supply chain management: A theoretical review, IUP Journal of Supply Chain Management, 7(1/2), 7-20.
Aliakbari, A. & Seifbarghy, M. (2011).A Supplier Selection Model for Social Responsible Supply Chain, Journal of Optimization in Industrial Engineering, 8, 41-53
Alireza, A. & Azadeh, S. (2020). Application of Fuzzy Analytical Hierarchy Process and Quality Function Deployment Techniques for Supplier's Assessment, Journal of Optimization in Industrial Engineering, Vol.13(2), 279- 289
Anupindi, R. & Akella, R. (1993), Diversification under supply uncertainty, Management Science, 39 (8), 944-963, doi.org/10.1287/mnsc.39.8.944
Azzouz, K., Arif, J. & Benboubker, M.B. (2021), Exploratory study of the role of logistics service providers in terms of traceability in the process of outsourcing of logistics’ Activities: case of Moroccan LSP, International Journal of Engineering Research in Africa, Vol 54, 187-208, doi.org/10.4028/www.scientific.net/JERA.54.187
Bender, P.S., Brown R.W., Issac, M.H & Shapiro J.F. (1985), Improving purchasing productivity at IBM with a normative decision support system, Interfaces, 15(3), 106-115, doi.org/10.1287/inte.15.3.106
Bounif, M.E. (2015), Optimisation à base de simulation pour le développement des systèmes décisionnels, Ph.D Thesis, Université de Msila, Algérie, (2015)
Buffa, F.P. & Jackson W.F.(1983), A goal programming model for purchasing planning, Journal of Purchasing and Materials Management, 19(3), 27-34, doi.org/10.1111/j.1745-493X.1983.tb00086.x
Chen, F.Y., Hum, S.H. & Sun, J. (2001). Analysis of third-party warehousing contracts with commitments, European Journal of Operational Research, 131(3), 603-610. doi.org/10.1016/S0377-2217(00)00102-8
Degraeve, Z. & Roodhooft, F.(1999), Improving the efficiency of purchasing process using total cost of ownership information: the case of heating electrodes at at cockerill Sambre S.A, European Journal of Operational Research, 112(1), 42-53, doi.org/10.1016/S0377-2217(97)00383-4
Fayoraman, V., Srivastava, R. & Benton B.C. (1999) Supplier selection and order quantity allocation: a comprehensive model, The journal of supply chain management, 35(1), 50-58, Spring. doi.org/10.1111/j.1745-493X.1999.tb00237.x
Frichi, Y., Jawab, F., Aboueljinane, L. & Boutahari, S. (2022), Development and comparison of two new multi-period queueing reliability models using discrete-event simulation and a simulation-optimization approach, Comput. Ind. Eng., vol 42, 108-178. 10.1016/j.cie.2022.108068.
Fulconis, F., Paché, G. & Roveill, G. (2011), La prestation logistique: origines, enjeux et perspectives, Cormelles-le- Royal: Editions EMS.
Ganeshan, R., Tyworth, J.E. & Guo, Y. (1999), Dual sourced supply chains the discount supplier option, Transportation Research Part E: Logistics and Transportation, 35(1), 11-23, doi.org/10.1016/S1366-5545(98)00020-9
Hajiabolhasani, Z., Marian, R. & Boland, J. (2018), Simulation-optimisation of a granularity controlled consumer supply network using genetic algorithms, Advances in Science, Technology and Engineering Systems Journal, 3(6), 455-468, doi.org/10.25046/aj030654
Hammami, A. (2013), Modélisation technico-économique d’une chaîne logistique dans une entreprise réseau. Ph.D Thesis, L’Ecole Nationale Supérieure des Mines de Saint-Etienne, Université Jean Monnet, France.
Horvath, L. (2001), Collaboration: the key to value creation in supply chain management, Supply Chain Management: An International Journal, 6(5),205-207. doi.org/10.1108/EUM0000000006039
Huang, M., Hu, X. & Zhang, L. (2011), A Decision method for distruption management problems in intermodal freight transport, Smart Innovation, Systems and Technologies, 13-21, doi.org/10.1007/978-3-642-22194-1_2
Ko, H.J. & Evans, G.W. (2007), A genetic algorithm-basedheuristics for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34, 2, 346-366, doi:10.1016/j.cor.2005.03.004
Ko, H.J., Ko, C.S.Q & Kim, T. (2006), A hybrid optimization/simulation approach for a distribution network design of 3PLs, Computers & Industrial Engineering, 50(4),440-449, doi.org/10.1016/j.cie.2005.03.006
Kumar, M., Vrat, P. & Shankar, R. (2006), A multi-objective 3PL allocation problem for fish distribution, International Journal of Physical Distribution & Logistics Management, 36(9),702-715, doi.org/10.1108/09600030610710863
Liao, Z., & Rittscher, J. (2007), Integration of supplier selection, procurement lot sizing and carrier selection under dynamic demand conditions, International Journal of Production Economics,107(2),502-51, doi.org/10.1016/j.ijpe.2006.10.003
Lieb, R. & Butner, K.(2007b), The year 2006 Survey: CEO perspectives on the current status and future prospects of the European third party logistics industry, Supply Chain Forum : An International Journal, 8(1) .
MacCormack, A.D., Newman L.J. III, & Rosenfield, D.B. (1994), The new dynamics of global manufacturing site location", 35(4), 69-80, Summer.
Malcom, S. (1997), Strategic purchasing & supply chain management, The institute of purchasing and supply, Finacial Times, Prentice Hall.
Marc-andré, C. (2012), La métaheuristique CAT pour le désign de réseaux logistiques déterminites et stochastiques. Ph.D Thesis, la Faculté des études supérieures et postdoctorales de l'Université Laval, QUÉBEC.
McGinnis, M.A. & Kohn, J.W. (2002), Logistics strategy revisited, , 23 (2), 1–17, doi.org/10.1002/j.2158-1592.2002.tb00023.x
Moore, E.W., Warmke, J.M. & Gorban, L.R. (1991), The indispensable role of management science in centralizingfreight operations at Reynolds metal company. Interfaces (USA), 21, 107-129, doi.org/10.1287/inte.21.1.107
Murray, A.T. (2016), Maximal coverage location problem: impacts, significance, and evolution, International Regional Science Review, 39(1), p. 5 27, doi: 10.1177/0160017615600222
Naji, M., & Younes, M. (2021), De la mesure de performance des chaines logistiques –Revue de littérature et taxonomie, Revue Internationale des Sciences de Gestion, 4(2), 1187 :1214.
Nam K., Chaudhury A. & Rao H. (1995). A mixed integer model of bidding strategies for outsourcing, European Journal Of Operational Research, 87, 257- 273. doi.org/10.1016/0377-2217(94)00147-5.
Narasimhan, R. & Staynoff, L.K.(1986), Optimizing aggregate procurement allocation decision, Journal of Purchasing and Materials Management,30, 23-30. doi.org/10.1111/j.1745-493X.1986.tb00153.x
Ngwenyama, O.K. & Bryson, N. (1999), Making the information systems outsourcing decision: A transaction cost approach to analyzing outsourcing decision, European Journal Of Operational Research, 115(2), 351-367. doi.org/10.1016/S0377-2217(97)00171-9
Paché, G. & Spalanzani A. (2007). (Eds), La gestion des chaînes logistiques multi-acteurs: perspectives stratégiques, Presses Universitaires de Grenoble, Grenoble, pp. 85-100.
Paché, G. (2009), Quels impacts de la crise sur la logistique ?, Revue Française de Gestion, 35: 51–57. doi:10.3166/rfg.193.51-57.
Pan, A.C. (1989), Allocation of order quantity among suppliers, Journal of Purchasing and Materials Management, 25(3), 36-39, doi.org/10.1111/j.1745-493X.1989.tb00489.x
Parunak, H.V.D, Savit, R., Riolo, R.L & Steven, J.C.(1999), DASCh: Dynamic analysis of supply chains, Center of Electronic Commerce Final Report.
R. Lieb, K. & Butner, K. (2007a), The North American third party logistics industry in 2006: the provider CEO perspective, Transportation Journal, 46(3), 40- 52.
Roy, B. (1996), Multicriteria methodology for decision aiding, Nonconvex optimization and its applications, Kluwer Academic Publishers.
Souza, R., William, L. & Lee, C.K. (2019), Marginalizing last mile logistics cost through 4th party milk run, Advances in Science, Technology and Engineering Systems Journal,4(4), 462-467, doi: 10.25046/aj040456
Suryawan, R.F., Basneldi, Fatchoelqorib, M., Septiano, R., Sari, L., Widodo, S., Yanthy Yosepha, S., Sugianto & Kusuma Devi, N., (2022), Two Meta-heuristic Algorithms for Solving Multi-objective Model for the Service Quality and Price in the Digital Supply Chain, Industrial Engineering & Management Systems, Vol 21, No 3, September 2022, pp.440-448.
Weber, C.A., & Current, J.R. (1993), A Multiobjective approach to vendor selection, European Journal of Operational Research, 68, pp 173-184.
Xie, S., Formonov, A., Thapit, A.A., Alshalal, M.H., Obeis, M.S.K., Sivaraman, R., Jabbar, A.H.,Chaudhary, P. & Fakri Mustafa, Y., Mushroom Supply Chain Network Design Using Robust Optimization Approach under Uncertainty, Industrial Engineering & Management Systems, Vol.21 No.3 pp.516-525
