Multi-Criteria Decision-Making Methods Application in Supply Chain Management: A Systematic Literature Review

Over the last decade, a large number of research papers, certified courses, professional development programs and scientific conferences have addressed supply chain management (SCM), thereby attesting to its significance and importance. SCM is a multi-criteria decision-making (MCDM) problem because throughout its process, different criteria related to each supply chain (SC) activity and their associated sub-criteria must be considered. Often, these criteria are conflicting in nature. For their part, MCDM methods have also attracted significant attention among researchers and practitioners in the field of SCM. The aim of this chapter is to conduct a systematic literature review of published articles in the application of MCDM methods in SCM decisions at the strategic, tactical and operational levels. This chapter considers major SC activities such as supplier selection, manufacturing, warehousing and logistics. A total of 140 published articles (from 2005 to 2017) were studied and categorized, and gaps in the literature were identified. This chapter is useful for academic researchers, decision makers and experts to whom it will provide a better understanding of the application of MCDM methods in SCM, at various levels of the decision-making process, and establish guidelines for selecting an appropriate MCDM method for managing SC activities

An ANFIS-based cache replacement method for mitigating cache pollution attacks in Named Data Networking

Named Data Networking (NDN) is a candidate next-generation Internet architecture designed to overcome the fundamental limitations of the current IP-based Internet, in particular strong security. The ubiquitous in-network caching is a key NDN feature. However, pervasive caching strengthens security problems namely cache pollution attacks including cache poisoning (i.e., introducing malicious content into caches as false-locality) and cache pollution (i.e., ruining the cache locality with new unpopular content as locality-disruption). In this paper, a new cache replacement method based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to mitigate the cache pollution attacks in NDN. The ANFIS structure is built using the input data related to the inherent characteristics of the cached content and the output related to the content type (i.e., healthy, locality-disruption, and false-locality). The proposed method detects both false-locality and locality-disruption attacks as well as a combination of the two on different topologies with high accuracy, and mitigates them efficiently without very much computational cost as compared to the most common policies

Joint Lot-Sizing and Transportation Collaboration for Global Supply Chain

International audienc

Context-Aware Business Processes Modelling: Concepts, Issues and Framework

International audienc

A Framework for Context-Aware Business Processes Modelling

International audienc

Assessment of Transportation Collaboration in Global Logistics

International audienc

Stochastic Inventory Control with Remanufacture and Environmental Considerations

International audienc

Utilizing energy transition to drive sustainability in cold supply chains: a case study in the frozen food industry

In alignment with the ever-growing interest in adopting sustainable practices, this paper devises a cold supply chain (CSC) planning model that integrates the three pillars of sustainability into the decision-making process while accounting for the shift towards clean energy sources. Interrelated decisions pertaining to production-distribution strategy, backorder and inventory levels, choice of truck type, and selection of third-party logistics (3PLs) providers are jointly optimized. For global CSCs in specific, such decisions are particularly sensitive to the energy sources of the refrigerated facilities and the accompanying levels of CO2 emissions generated. As such, a multi-objective mixed-integer non-linear programming (MINLP) model is developed and then solved via the weighted-sum method. In essence, the model seeks to operationalize sustainability goals by considering the rapidly evolving transition in energy sources across different regions when deciding on which 3PLs to engage in a contractual agreement with while adjusting the production and distribution strategy accordingly. The practical relevance of the model is illustrated using a case study drawn from the North American frozen food industry. The conducted trade-off analysis indicates the possibility of obtaining a drastic improvement of 86% in jobs’ stability levels (social measure) with a maximum cost increase of around 9% as compared to the economic measure. Furthermore, the analysis reveals that it is possible to reduce 71% of CO2 emissions while attaining 63% reduction in worker variations at the expense of only 4.47% cost increase once compared to solely optimizing the economic objective

An Integrated Logistics Model for Environmental Conscious Supply Chain Network Design

Operations Research has addressed a variety of environmental problems outside the traditional supply chain management area such as remanufacturing, reverse logistics, and waste management. Supply chain sustainability, which includes designing green supply chains, will gain much more attention in the future. Indeed, most companies are still in the early stage of considering a green initiative. Traditionally, optimization models for supply chain network design looked to different strategic network alternatives, and analyze the trade-offs between logistics costs and service requirements. Today, with the strong emphasis in reducing greenhouse gas footprint, the integration of such consideration into the supply chain network design phase will provide to companies much more visibility on how to manage efficient, effective, and green supply chains. In this paper, a mathematical programming model for environmental conscious supply chain network design is introduced with the explicit inclusion of carbon emission cost. By considering the greenhouse gases emissions cost together with traditional logistics costs, the problem is formulated as a single objective optimization program. The methodology uses mixed integer linear programming modeling technique to deal with different strategic decisions, including supplier and subcontractor selection, product allocation, capacity utilization, and assignment of transportation links required to satisfy market demand. This new formulation provides decision makers with a quantitative decision support system to understand the tradeoffs between the total logistics cost and the carbon footprint reduction