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This book introduces students on Multiple Criteria Decision Aiding and Making courses to practical, real-world cases. Each case study introduces a problem or situation together with a method, and a description and explanation of a computer application. In this sense each chapter is based on four pillars: the problem, the model building, the methods and their implementation. The book presents and elaborates a rich and comprehensive set of practical problems comprising multiple criteria, including numerous approaches for their solution, for decision support or decision aid. It complements…mehr

Produktbeschreibung
This book introduces students on Multiple Criteria Decision Aiding and Making courses to practical, real-world cases. Each case study introduces a problem or situation together with a method, and a description and explanation of a computer application. In this sense each chapter is based on four pillars: the problem, the model building, the methods and their implementation. The book presents and elaborates a rich and comprehensive set of practical problems comprising multiple criteria, including numerous approaches for their solution, for decision support or decision aid. It complements traditional textbooks and lecture material by employing case studies to promote a deeper understanding of the investigated concepts and help students apply these methods to other areas.
Autorenporträt
Sandra Huber is a postdoctoral researcher at the Logistics-Management Department at the Helmut-Schmidt-University in Hamburg, Germany since July 2016. In 2016 she was awarded with her PhD degree with a thesis on the topic "Interactive multiobjective optimization in supply chain management - local search strategies for rich vehicle routing problems". For a research period she visited the research institute CIRRELT in Montréal, Canada. Her research area is in decision support and supply chain management. She is particularly interested in multi-objective combinatorial optimization, interactive approaches, heuristics for vehicle routing problems and the simulation of preference information.  Martin Josef Geiger is a full professor of Business Administration/ Logistics Management at HSU Hamburg, Germany. His research interests primarily lie in (NP-) hard combinatorial optimization problems with applications in routing, scheduling, and timetabling. In this context, he is particularly focusing on multi-criteria issues, interactive methods and decision support systems, and the efficient implementation of modern heuristics in running systems. He has made numerous contributions to scientific journals and conferences, and has served as organizer of the 2013 Summer School on MCDA/M and the 23rd International Conference on Multiple Criteria Decision Making MCDM 2015.   Adiel Teixeira de Almeida is Full Professor of management engineering at Universidade Federal de Pernambuco and founding coordinator of the CDSID (Center for Decision Systems and Information Development). Before his current position, he worked in business organizations as engineer and manager. He holds a PhD in management engineering from The University of Birmingham, UK. His main interests are in decision-making related to multiple objectives and group decision problems, which includes methodological issues and applications. He authored or co-author over 100 scientific papers in reviewed journals. He serves on the editorial board of scholarly journals, such as: Group Decision and Negotiation, IMA Journal of Management Mathematics, International Journal of Decision Support System Technology and EURO Journal on Decision Processes. He has been an active member of main societies related to MCDM/A (Multicriteria Decision Making and Aid) and Group Decision. Currently, he serves as VP for membership the Group Decision and Negotiation Section of INFORMS and the Executive Committee of the International Society on Multiple Criteria Decision Making and he is an Associate Research Fellow of the Institute of Mathematics and its Applications (FIMA). He also received in 2017 the INFORMS GDN Section Award.