Hoda Davarzani

Quantitative models for managing supply chain risks: A review

As supply chain risk management has transitioned from an emerging topic to a growing research area, there is a need to classify different types of research and examine the general trends of this research area. This helps identify fertile research streams with great potential for further examination. This paper presents a systematic review of the quantitative and analytical models (i.e. mathematical, optimization and simulation modeling efforts) for managing supply chain risks. We use bibliometric and network analysis tools to generate insights that have not been captured in the previous reviews on the topic. In particular, we complete a systemic mapping of the literature that identifies the key research clusters/topics, interrelationships, and generative research areas that have provided the field with the foundational knowledge, concepts, theories, tools, and techniques. Some of our findings include (1) quantitative analysis of supply chain risk is expanding rapidly; (2) European journals are the more popular research outlets for the dissemination of the knowledge developed by researchers in United States and Asia; and (3) sustainability risk analysis is an emerging and fast evolving research topic.

Developing a supply chain disruption analysis model: Application of colored Petri-nets

As a result of globalization in the past two decades, supply chains are encountering more unknown conditions and risks. One important category of risks is disruptions that block material flowing through a supply chain and that may even result in end-product manufacturing failure. This paper uses a Petri nets-based model as a tool to understand the dissemination of disruptions and to trace the operational performance of a supply chain. The presented approach models how changes propagate through a supply chain and calculates the impact of disruptions on supply chain attributes by concluding the states that are obtainable from a given initial status in the supply chain.

Planning of complex supply chains: A performance comparison of three meta-heuristic algorithms

Abstract Businesses have more complex supply chains than ever before. Many supply chain planning efforts result in sizable and often nonlinear optimization problems that are difficult to solve using standard solution methods. Meta-heuristic and heuristic solution methods have been developed and applied to tackle such modeling complexities. This paper aims to compare and analyze the performance of three meta-heuristic algorithms in solving a nonlinear green supply chain planning problem. A tactical planning model is presented that aims to balance the economic and emissions performance of the supply chain. Utilizing data from an Australian clothing manufacturer, three meta-heuristic algorithms including Genetic Algorithm, Simulated Annealing and Cross-Entropy are adopted to find solutions to this problem. Discussions on the key characteristics of these algorithms and comparative analysis of the numerical results provide some modeling insights and practical implications. In particular, we find that (1) a Cross-Entropy method outperforms the two popular meta-heuristic algorithms in both computation time and solution quality, and (2) Simulated Annealing may produce better results in a time-restricted comparison due to its rapid initial convergence speed.

Socio-environmental performance of transportation systems

Purpose – The purpose of this paper is to identify and categorize the social and environmental impacts of transportation systems, and address the appropriate solutions to mitigate and manage these impacts in order to achieve sustainability. Design/methodology/approach – This research performs a comprehensive literature review to suggest a framework on socio-environmental impacts of transportation and related solutions. The proposed framework is analyzed through quantitative methods and a survey study in freight transport. Findings – Findings support the direct relation of potential solutions and socio-environmental impacts of transportation. All four categories of solutions (technological, socio-economic and political, cultural and behavioral, and infrastructure related) reveal direct impact on reduction of environmental impacts. However only technological solutions were found to be influential on social impacts of the transportation. Originality/value – To the best of the authors’ knowledge there has not...

Understanding econo-political risks: impact of sanctions on an automotive supply chain

Purpose – The purpose of this paper is to introduce econo-political risks (EPRs) to supply chains (SCs). Based on case data from an automotive SC, this research identifies the mechanisms through which a subset of EPRs influences SC operations and outcomes. Design/methodology/approach – An exploratory case study method is employed for theory development. Interviews with SC professionals of three case companies were the primary data source. Company documents, archival records, and direct observation provided further insights into how EPRs are perceived, how they impact a SC, how SC actors react to them, and what the overall performance results are. Findings – The research identifies EPRs in terms of scope (flow of material, money, and knowledge) and time, and provides concrete examples, along with the channels through which their impact unfolds, and the responses available to SC actors. The authors find secondary impacts of EPRs through economic and regulatory channels to be significant, and bankruptcy, strategic reorientation, and single sourcing are common outcomes. By elaborating on the mechanisms through which sanctions impact upon SCs, and the feasible response trajectories, this research can assist SC actors with more effective management of EPRs. Originality/value – This paper is novel for three reasons: first, it introduces EPRs to research into supply chain risk management (SCRM); second, it addresses SC risks in a developing country, a topic largely missing from the literature; and finally, this research focuses on post-event SC risks, whereas the bulk of SCRM literature focuses on the pre-event phase.

Supply Network Design

In this chapter we will have a general overview of distribution networks and some of their models as well; finally this chapter concludes with national and international aspects of this issue and some related case studies.

A Review of the Literature of Green Ports and Maritime Logistics

Port operations and maritime logistics represent major sources of air pollution. Given the recent greening initiatives and developments in this area and correspondingly a geometric growth in the number of academic publications, this chapter aims to (a) provide some statistics of the key journals, authors and institutions that have contributed to the field, and (b) identify the primary research topics investigated. The proposed literature classification and analysis can help interested researchers and students establish their research agendas in this emerging area of study and investigation.

Capacity Allocation and Pricing for Take-or-Pay Reservation Contracts

This paper uses a bi-level optimization model to formulate a specific type of capacity reservation contracts, namely take-or-pay contracts, where a buyer reserves a portion of a supplier’s capacity before demand is realized with discounted price. At first, we formulate the lower-level problem and solve a non-linear optimization model where a buyer decides on the amount of capacity to be reserved given the discounted and normal unit capacity price, demand probability distribution and maximum available capacity. Afterwards, we construct the upper-level model where there are a supplier and multiple buyers and the supplier must choose the discounted price and maximum available capacity for each of the buyers. Enforced by the behaviour of the model, we create a bi-level real-valued genetic algorithm to find good solutions for the model.

Orchestrating supply and demand chain management processes

Demand chain management is becoming more important for both academics and practitioners and linking it with supply oriented view is one of the challenges in this area. This paper seeks to provide a structured framework from process oriented view to make orchestration between supply chain management and demand chain management through deep literature review and aggregation of experts’ idea via AHP analysis. For making this framework more and more practical one of the most accepted and well-defined process-based structure of supply chain (named as GSCF) has been selected as the basis for this research. Moreover, the paper gives in depth inside in differences between SCM and DCM for managers and practitioners to clarify what exactly they are and which parts of a firm are engaged in incorporating their activities.

A New Approach for Bacillus Colonies Recognition: Application of Intuitionistic Fuzzy Sets Theory

This paper proposes a new approach for medical diagnosis based on laboratory empirical data using fuzzy set theory. The presented approach is based on intuitionistic fuzzy set (IFSs) theory as a special kind of fuzzy set using two new distance measures between intuitionistic fuzzy sets as a tool in pattern recognition. We will apply them in a part of progress of medical diagnosis in order to recognize Bacillus colonies and then we compare its results with similar measures in regular fuzzy. Numerical results show that the proposed measures are more applicable in medical diagnosis than the similar measures in regular fuzzy ones.