Hybrid Simulation Based Optimization for Supply Chain Management


Book Description

Supply chain management (SCM) has been recognized as one of the key issues in the process industry. The growing size of the distributed supply chain structures, market dynamics and variability involved in the internal operations pose a challenge to efficiently managing the whole network. Globalization of supply chains and advances in information technology have led to a greater need for integrated operations as they have caused a more distributed network with potentially larger number of customers. It is essential that the various bodies constituting the supply chain operate in an integrated manner and their activities are synchronized towards a common goal. Thus, there is a need for efficient integration of information and decision making among the various functions of the supply chains. The growing need for integrated information and decision-making necessitates the development of a framework which allows the different entities of a supply chain to have access to a common information system as well as provides them with advanced decision-making tools. With the advancements in information technology, it is possible for supply chain members to share information and several such tools are also commercially available. However there is a need to combine intelligent decision making with information sharing to develop the required framework. The main objective of this dissertation is the development of novel methodologies that will facilitate intelligent decision-making and their application in the analysis of supply chains for chemical industries. Simulation models are used to depict supply chain dynamics so that they represent the decision-making by various entities. In order to obtain improved decision-making, a hybrid simulation based optimization framework is proposed. The framework considers the decision rules followed by the different entities and guides the simulation model towards improved solutions. The benefits of these methodologies include a more realistic representation of supply chain dynamics and reduced computational times for large-scale problems. The framework is applied to a number of case studies. Uncertainty in supply chain is also considered and the framework is used to determine the flexibility of the supply chain and manage risk under uncertainty. A derivative free optimization method is also proposed which has been applied to optimize the performance of a multi-enterprise supply chain network.




Conditional Monte Carlo


Book Description

Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry.




Supply Chain Simulation


Book Description

Supply Chain Simulation allows readers to practice modeling and simulating a multi-level supply chain. The chapters are a combination of the practical and the theoretical, covering: knowledge of simulation methods and techniques, the conceptual framework of a typical supply chain, the main concepts of system dynamics, and a set of practice problems with their corresponding solutions. The problem set includes illustrations and graphs relating to the simulation results of the Vensim® program, the main code of which is also provided. The examples used are a valuable simulation tool that can be modified and extended according to user requirements. The objective of Supply Chain Simulation is to meet the demands of supply chain simulation or similar courses taught at the postgraduate level. The “what if” analysis recreates different simulation scenarios to improve the decision-making process in terms of supply chain performance, making the book useful not only for postgraduate students, but also for industrial practitioners.




Quantitative Models for Value-Based Supply Chain Management


Book Description

​​​​​​​Supply chain management (SCM) strives for creating competitive advantage and value for customers by integrating business processes from end users through original suppliers. However, the question of how SCM influences the value of a firm is not fully answered. Various conceptual frameworks that explain the coherence of SCM and company value, comprehended as value-based SCM, are well accepted in scientific research, but quantitative approaches to value-based SCM are found rather seldom. The book contributes to this research gap by proposing quantitative models that allow for assessing influences of SCM on the value of a firm. Opposed to existing models that limit the observation to chosen facets of SCM or selected value drivers, this holistic approach is adequate to • reflect configurational and operational aspects of SCM, • cover all phases of the product life cycle, • financially compare value impacts of profitability-related and asset-related value drivers, and • assess influences of dynamics and uncertainties on company value.​




Agent Based Simulation Approach to Assess Supply Chain Complexity and Its Impact on Performance


Book Description

In today's global business environment, the intense competition, the changing and uncertain conditions, and the increasing customer's requirements are challenges for the companies' operational efficiency and profitability. In this context, companies highlight the importance of supply chain design and its holistic understanding in order to achieve and sustain competitive strengths. This book analyses supply chains as complex systems, whose performance is characterized by their structural configuration and emergent behaviour. The author analyses the supply chain structure and behaviour within the scope of complexity science. He focuses on supply chain complexity by means of a literature review and an empirical research, which give insights into the impact of complexity on supply chain performance. Moreover, within this book the supply chain is modelled as a complex system by considering the non-linear relationships of its geo-positioned elements. Finally, an agent based model is developed for the generic supply chain simulation, which allows assessing the impact of complexity on supply chain performance and characterizing the behaviour of supply chain designs. The materials presented in this book contribute to the understanding and management of supply chain complexity. This work complements existing complexity frameworks with a holistic analysis of complexity's impact on the performance of supply chain participants and their network. The findings of this work are relevant for researchers interested in characterizing supply chain phenomena by enabling them to model supply chain structures and to simulate their emergent behaviour. Practitioners can benefit from the provided model and simulation platform by allowing them to dynamically assess the performance of their supply chain designs and strategy definitions. By these means, they improve their decision-making and business profitability. In all, this book contributes towards the development of artificial intellig




Supply Chain Analytics


Book Description

This textbook offers a detailed account of analytical models used to solve complex supply chain problems. It introduces a unique risk analysis framework that helps the reader understand the sources of uncertainties and use appropriate models to improve decisions in supply chains. This framework illustrates the complete supply chain for a product and demonstrates the supply chain's exposure to demand, supply, inventory, and financial risks. Step by step, this book provides a detailed examination of analytical methods that optimize operational decisions under different types of uncertainty. It discusses stochastic inventory models, introduces uncertainty modeling methods, and explains methods for managing uncertainty. To help readers deepen their understanding, it includes access to various supplementary material including an online interactive tool in Python. This book is intended for undergraduate and graduate students of supply chain management with a focus on supply chain analytics. It also prepares practitioners to make better decisions in this field.




Operations Research Proceedings 2015


Book Description

This book gathers a selection of refereed papers presented at the “International Conference on Operations Research OR2015,” which was held at the University of Vienna, Austria, September 1-4, 2015. Over 900 scientists and students from 50 countries attended this conference and presented more than 600 papers in parallel topic streams as well as special award sessions. Though the guiding theme of the conference was “Optimal Decision and Big Data,” this volume also includes papers addressing practically all aspects of modern Operations Research.




Quantitative Approaches to Distribution Logistics and Supply Chain Management


Book Description

Increasing customer needs, the globalization of markets and the evolution of e-commerce add to the complexity of logistic processes. In today's business, it is well understood that an effective management of logistic processes is impossible without the use of computer-based tools and quantitative methods. This book presents in a systematic way quantitative approaches to distribution logistics and supply chain management. The main orientation of the book is towards practical problem solving, and numerous case studies and practical applications are presented. The topics covered include: supply chain management, revers logistics, e-commerce, facility location and network planning, vehicle routing, warehousing, inventory control.




Inventory Optimization


Book Description

In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple—yet powerful—framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter. Events around the book Link to a De Gruyter Online Event in which the author Nicolas Vandeput together with Stefan de Kok, supply chain innovator and CEO of Wahupa; Koen Cobbaert, Director in the S&O Industry practice of PwC Belgium; Bram Desmet, professor of operations & supply chain at the Vlerick Business School in Ghent; and Karl-Eric Devaux, Planning Consultant, Hatmill, discuss about models for inventory optimization. The event will be moderated by Eric Wilson, Director of Thought Leadership for Institute of Business Forecasting (IBF): https://youtu.be/565fDQMJEEg