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Increasing Sustainability of Logistic Networks by Reducing Product Losses: A Network DEA Approach 时间:2018-11-13 16:50 来源:未知作者:admin 点击: 次 Abstract:This paper considers a multiproduct supply network, in which losses (e.g., spoilage of perishable products) can occur at either the nodes or the arcs. Using observed data, a Network Data Envelopment Analysis (NDEA) approach is proposed to assess the efficiency of the product flows in varying periods. Losses occur in each process as the observed output flows are lower than the observed input flows. The proposed NDEA model computes, within the NDEA technology, input and output targets for each process. The target operating points correspond to the minimum losses attainable using the best observed practice. The efficiency scores are computed comparing the observed losses with the minimum feasible losses. In addition to computing relative efficiency scores, an overall loss factor for each product and each node and link can be determined, both for the observed data and for the computed targets. A detailed illustration and an experimental design are used to study and validate the proposed approach. The results indicate that the proposed approach can identify and remove the inefficiencies in the observed data and that the potential spoilage reduction increases with the variability in the losses observed in the different periods.
1. Introduction
Economic growth and globalisation represent major challenges for the logistics sector. As larger quantities of products are transported over greater distances, more complex logistics networks have to be designed to guarantee that all material will arrive safely and on time [1, 2]. Designing such networks involves many different decisions. Altiparmak et al. [3] include in this process the definition of manufacturing plants’ characteristics (i.e., their capacity and types of production), the number of warehouses and distribution centres used to store and forward the products, their location, defining the distribution channels and retailers to serve, and determining the quantity of products flowing through each edge in the network.
Normally, for mathematical modelling purposes, the logistics network is represented using a directed graph. The nodes correspond to the suppliers, manufacturing plants, warehouses, wholesalers, and retailers, while the arcs represent the product flows among nodes. Additionally, when there are restrictions on the corresponding product flows, capacity limits are attached to nodes and arcs. In this way, all decisions previously listed can be translated into the model and defined using a graph.
The complexity of logistics network design has attracted a great deal of research, mainly looking to optimise the material flows. From some review reports (e.g., [4, 5]) it can be derived that existing papers have analysed different design objectives, but almost always these are endeavouring to reduce costs (or, alternatively, maximize profits). However, the costs aspect, although always important, is not the only factor to be taken into consideration when deciding where to source and how to deliver and move products. Other factors are also relevant, such as providing a high service level and sustainability. Issues such as the environmental impact of logistics operations have come under the scrutiny of the logistics community, opening a new research field usually referred to as green logistics [6]. Events such as terrorist acts, natural disasters (floods, hurricanes, etc.), nuclear accidents, or labour strikes have also created interest in the design of more resilient logistics networks. Finally, designing logistics networks able to guarantee a high service level is also a main goal of many companies, for which their competitive strategy is aligned with that goal. Therefore, considering these types of alternative objectives is becoming more common when studying logistics networks, with some researchers considering more than one of these objectives and proposing a multiobjective approach [7, 8].