Agent Based Simulation Approach To Assess Supply Chain Complexity And Its Impact On Performance

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

As the customer is demanding more sustainable and affordable products, the supply chains have to find innovative ways to fulfill this need. In this context, collaboration as well as optimization methods are becoming even more evident to enhance supply chain structure to an efficient and sustainable approach. While collaboration and optimization increase complexity and susceptibility, risk management needs to be applied concurrently. This volume, edited by Wolfgang Kersten, Thorsten Blecker and Christian Ringle, provides valuable insights into: - Sustainability in Logistics - Sustainability and collaboration practices - Supply chain risk management - Optimization methods in supply chain management. This volume addresses timely and relevant topics. Both researchers and practitioners are addressed and can obtain background information from current distributions by international authors presenting a state of the art research overview.

Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.

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.

This book explores how complexity science and social simulation can be used to improve and inform policy-making in both research and innovation. Beginning with an introduction to conceptual definitions of complexity science and social simulation, the book demonstrates the validity of the underlying integrated research framework used throughout. It is then divided into two parts, with the first investigating the effects and impacts of policy making on the structure, composition and outputs of research and innovation networks using the agent-based SKIN platform (Simulating Knowledge Dynamics in Innovation Networks, http://cress.soc.surrey.ac.uk/SKIN/). The second half of the book discusses a research initiative funded by the Irish government focusing on innovation policy simulation for economic recovery. This consists of empirical research on Irish research and innovation networks, and SKIN-based simulations of technology transfer issues and the commercialization of research in areas with high potential for innovation and economic growth. The book concludes with reflections on the maturity and utility of an approach combining complexity science and social simulation for research and innovation policy. Joining Complexity Science and Social Simulation for Innovation Policy will be of particular interest to scientists concerned with innovation and complex systems, including economists, sociologists, and complexity researchers, as well as students and practitioners, such as innovation policymakers and innovation business managers.

This two-volume set of LNAI 12798 and 12799 constitutes the thoroughly refereed proceedings of the 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, held virtually and in Kuala Lumpur, Malaysia, in July 2021. The 87 full papers and 19 short papers presented were carefully reviewed and selected from 145 submissions. The IEA/AIE 2021 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include the following: Part I, Artificial Intelligence Practices: Knowledge discovery and pattern mining; artificial intelligence and machine learning; sematic, topology, and ontology models; medical and health-related applications; graphic and social network analysis; signal and bioinformatics processing; evolutionary computation; attack security; natural language and text processing; fuzzy inference and theory; and sensor and communication networks Part II, From Theory to Practice: Prediction and recommendation; data management, clustering and classification; robotics; knowledge based and decision support systems; multimedia applications; innovative applications of intelligent systems; CPS and industrial applications; defect, anomaly and intrusion detection; financial and supply chain applications; Bayesian networks; BigData and time series processing; and information retrieval and relation extraction

26th European Symposium on Computer Aided Process Engineering contains the papers presented at the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event held at Portorož Slovenia, from June 12th to June 15th, 2016. Themes discussed at the conference include Process-product Synthesis, Design and Integration, Modelling, Numerical analysis, Simulation and Optimization, Process Operations and Control and Education in CAPE/PSE. Presents findings and discussions from the 26th European Society of Computer-Aided Process Engineering (ESCAPE) Event