This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address risk-neutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on innovative, computationally efficient portfolio approaches to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on real-world supply chain disruption management problems, illustrate the material presented and provide managerial insights. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into five main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply (and demand) portfolios and scheduling; and Part V addresses disruption management of information flows in supply chains.

This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address riskneutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on integrated disruption mitigation and recovery decision-making and innovative, computationally efficient multi-portfolio approach to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on realworld supply chain disruption management problems, illustrate the material presented and provide managerial insights. Many propositions formulated in the book lead to a deep understanding of the properties of developed stochastic mixed integer programs and optimal solutions. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into six main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply and demand portfolios and production and inventory scheduling, Part V deals with selection of resilient supply portfolio in multitier supply chain networks; and Part VI addresses selection of cybersecurity safequards portfolio for disruption management of information flows in supply chains.

Volume 20 of Applications of Management Science focuses on the application of management science methodologies, data envelopment analysis and multi-criteria decision making.

A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.

This book offers an introduction to structural dynamics, ripple effect and resilience in supply chain disruption risk management for larger audiences. In the management section, without relying heavily on mathematical derivations, the book offers state-of-the-art concepts and methods to tackle supply chain disruption risks and designing resilient supply chains in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering background. In the technical section, the book constitutes structural dynamics control methods for supply chain management. Real-life problems are modelled and solved with the help of mathematical programming, discrete-event simulation, optimal control theory, and fuzzy logic. The book derives practical recommendations for management decision-making with disruption risk in the following areas: How to estimate the impact of possible disruptions on performance in the pro-active stage? How to generate efficient and effective stabilization and recovery policies? When does one failure trigger an adjacent set of failures? Which supply chain structures are particular sensitive to ripple effect? How to measure the disruption risks in the supply chain?

This book offers an introduction to the ripple effect in the supply chain for a broad audience comprising recent developments. The chapters of this handbook are written by leading experts in supply chain risk management and resilience. For the first time, the chapters present in their synergy a multiple-faceted view of the ripple effect in supply chains, while considering organization, optimization, and informatics perspectives. Ripple effect describes the impact of a disruption propagation on supply chain performance, structural designs and operational parameters. The ripple effect manifests when the impact of a disruption cannot be localized and cascades along the supply chain. The resulting structural dynamics can lead to capacity and demand fulfilment downscaling and negatively influence the firm’s financial and operational performance. The book delineates major features of the ripple effect and methodologies to mitigate the adverse impact of supply chain disruption propagation and to recover in case of severe disruptions. The book provides fresh insights for supply chain management and engineering regarding the following questions: - In what circumstance does one failure cause other failures? - Which structures of the supply chain are especially susceptible to the ripple effect? - What are the typical ripple effect scenarios and what are the most efficient ways to respond them? Distinctive Features: • It considers ripple effect in the supply chain from an multi-disciplinary perspective• It offers an introduction to ripple effect mitigation and recovery policies in the framework of disruption risk management in supply chains for a broad audience• It integrates management and engineering perspectives on disruption risk management in the supply chain• It presents innovative optimization and simulation models for real-life management problems• It considers examples from both industrial and service supply chains• It reveals decision-making recommendations for tackling disruption risks in the supply chain in proactive and reactive domains.

In this book, a risk management approach starts off by discussing important issues related to managing supply chain disruption risks from various perspectives during VUCA times. It explores the essence and principles relating to managing these risks and provides the framework and multi-goal model groups for managing such unknown-unknown risks and subsequent disruptions at a global scale. The book explores and presents the latest developments across different emerging topics in supply chain risk and disruption management. These include (i) an overview of supply chain risk, and disruption management tools, techniques, and approaches, (ii) a review on uncertainty modeling for decentralized supply chain systems, (iii) supply chain deep uncertainties and risks - the 'new normal', (iv) emergent technologies for supply chain risk and disruption management, (v) supply chain resilience strategies for times of unprecedented uncertainty, (vi) the role of blockchain in developing supply chain resilience against disruptions, (vii) a qualitative study on supply chain risk management adopting blockchain technology, (viii) assessment of risks and risk management for agriculture supply chain, (ix) resilience of agri-food supply chains: Australian developments after a decade of supply and demand shocks, (x) prioritization of risks in the pharmaceutical supply chains (xi) improving medical supply chain disruption management with the blockchain technology, and (xii) impacts of resilience practices on supply chain sustainability. The book contributes significantly to the growing body of knowledge concerning the theory and practice of managing supply chain risks and disruptions in strategic management, operations and supply chain, and sustainability literature. It presents contemporary, innovative and latest developments in applying smart management tools, techniques and approaches for managing supply chain risk and disruption and future-proofing supply chains to become agile, resilient and sustainable.

Adoption of new technologies in logistics and supply chain processes is crucial for the continued effectiveness of supply chains. Technology has the potential to address the issue of logistics and supply chain visibility throughout the supply chain, from raw materials through manufacturers and end users. When properly implemented, improved forecasting of inventory levels, employee productivity, adequate accountability, and higher warehouse savings are all possible. Additionally, businesses must upskill their supply chain workers and recruit and manage digital talent in cross-functional teams. The Handbook of Research on Promoting Logistics and Supply Chain Resilience Through Digital Transformation discusses the ways in which global logistics and supply chains have been severely disrupted by digital technology transformation. The book helps policymakers in designing a resilient framework that can absorb external shocks like the COVID-19 pandemic and also enhances the performance and operational capability of the logistics and supply chain network. Covering topics such as oil and gas maintenance support, stakeholder management, and business optimization strategy, this major reference work is essential for logistics professionals, business leaders and executives, IT managers, government officials, manufacturers, students and faculty of higher education, librarians, researchers, and academicians.

Methods of advanced data collecting and their analysis, models which help with decision problems as well as technical solutions which improve the integrity of contemporary transport systems at urban area are only some of many problems connected with integration in passenger and freight transport which have been discussed in this book. The book expresses case study-based scientific and practical approach to the problems of contemporary transport systems. The proposed methods and models enable a system approach to assess current solutions. In turn, implementation proposals may support the improvement of the integrity of individual elements of transport systems, and thus increase its effectiveness on the global scale. With regard to the research results discussed and the selected solutions applied, the book primarily addresses the needs of three target groups: • Scientists and researchers (ITS field) • Local authorities (responsible for the transport systems at the urban and regional level) • Representatives of business (traffic strategy management) and industry (manufacturers of ITS components). This book gathers selected papers presented at the 15th Scientific and Technical Conference “Transport Systems. Theory and Practice” organised by the Department of Transport Systems and Traffic Engineering at the Faculty of Transport of the Silesian University of Technology. The conference was held in Katowice, Poland on September 17–19, 2018.