رویکرد بالا به پایین و یک سیستم پشتیبانی تصمیم گیری برای طراحی و مدیریت شبکه های لجستیک

This paper presents an original top-down approach, made of original models and solving methods, and a decision support system (DSS) for the execution of the strategic planning, the tactical planning and the operational planning in a multi-echelon multi-stage multi-commodity and multi-period production, distribution and transportation system. The DSS is a software platform useful for the design, management and control of real instances. It can efficiently supports the decision making process of logistic managers and planners of large enterprises as multi-facilities companies and production–distribution networks. A significant case study is illustrated. The results obtained by the application of different problem settings are compared and discussed.

Supply chain management (SCM) is the process of planning, implementing and controlling the operations of a supply chain (SC) in an efficient way (Melo et al., 2009). SCM is “the integration of key business processes from end-user through original suppliers” (Lambert et al., 1998). Very important issues for SCM are the definition of the best possible network configuration and the identification of the best management rules and operational procedures. Both are objects of this manuscript. Fig. 1 presents a distribution network made of three stages and four levels. The generic stage involves two consecutive levels of entities based on the relationship supplier-customer. The available levels are the sources, named also production plants (at the first level), the central distribution centres (CDCs) (at the second level), the regional distribution centres (RDCs) representing the third level, and finally the customers/consumers points of demand (Pods) at the fourth level. This is an example of a generic distribution network and it is the basic configuration adopted in this study and treated by the proposed models, methods and DSS as discussed below.The aim of the manuscript is the development of an original top-down and multi-step original approach for the effective design, management and control of multi-echelon logistic production–distribution networks, typical of large enterprises made of thousands of entities at different levels of the system. The proposed approach has been implemented in a DSS, named LD-LogOptimizer, which supports the decisions making process on strategic, tactical and operational issues. This software platform can be applied to the design, management and control of real and complex instances and can efficiently support managers, planners and practitioners from industry and large enterprises as multi-facilities companies and distribution–production networks. The proposed approach and DSS are based on the application of original models and solving methods, including both optimization and heuristic techniques. A significant case study, as rarely presented by the literature, is illustrated: the results obtained by a multi-scenario what-if analysis and different problem settings are reported and discussed. The remainder of this paper is organized as follows. Section 2 presents a review of the literature on models and tools for the design, management and control of a distribution system. Section 3 illustrates the proposed top-down multi-step approach for strategic, tactical and operational planning of a logistics network. Section 4 presents an original and effective MILP optimization model for the strategic planning. Similarly, Section 5 presents a multi-period optimization MILP model for the tactical planning. Section 6 illustrates an effective heuristic approach for the operational planning and capacitated vehicle routing. Section 7 presents a significant case study. It demonstrates the effectiveness of both the proposed approach and DSS. Finally, Section 8 discusses conclusions and further research.

Many companies operating worldwide have to simultaneously face some of the following critical issues: the determination of the best number and location of production and/or distribution plants, e.g. distribution centres, transit points and hubs, the assignment of customers and points of demand to distributors and wholesalers, the management of inventory systems, the determination of the best transportation mode, the vehicles fleet management with attention to loading, scheduling & routing criteria, etc. The decisions at strategic, tactical, and operational planning levels are significantly interdependent in a logistic distribution system. Having unified tools that embed strategic, tactical and operational levels is an old idea but very few works manage to propose an efficient integrated approach. The proposed paper deals with an original top-down approach (1) for the strategic, tactical and operational planning of a logistic network. The approach is made of original models (2), effective solving methods and algorithms (3), and an original DSS (4) for real applications in very complex environments. This paper present a real application (5), rarely presented in the literature. It demonstrates the effectiveness of the proposed models, methods and tools. The basic contribution of this paper is the originality of the proposed effective approach, models, methods, DSS and application to planning and design a logistic network. These models and tools for planning and design logistic networks are effective in presence of hundreds of entities among sources, production plants, distribution centres, wholesalers, customers, etc. This new and systematic approach to the design, management and control of logistic networks is based on the simultaneous application of different mathematical modelling approaches, e.g. mixed integer linear programming, cluster analysis, and heuristics algorithms. The approach and software platform can support the logistic manager of a multi-echelon production/distribution system to best move products from the source levels to the destination points, by the coordination of the managers of different facilities, e.g. distribution centres, production plants, wholesalers, and dealers. The coordination of the logistic decisions can guarantee the “best possible and feasible” configuration and management of the whole system. The NP computational complexity and the large number of the decisions at each level (strategic, tactical and operational) force the decision maker to renounce to the identification of the best feasible solution even if optimization models and solving methods are applied. For example at the tactical level a mixed integer linear programming model is proposed and adopted: a solver can identify the optimal solution to this decisional step, but in presence of very large and complex instances it is necessary to adopted simplified models and solutions. Further research has to focus on the development of new integrated models and tools for planning, design, management and control of complex logistic networks to find global solutions as closed as possible to the optimum. The research has to present and discuss new applications and what-if experimental analyses including the definition of benchmarks and case studies useful to further research. Modern companies need tools capable to integrate distribution issues with other complex logistics problems, e.g. order picking and warehousing management and optimization, inventory management, production scheduling and sequencing, etc. This is the ambitious challenge for the future research.