This volume collects peer-reviewed short papers presented at the Optimization and Decision Science conference (ODS 2022) held in Florence (Italy) from August 30th to September 2nd, 2022, organized by the Global Optimization Laboratory within the University of Florence and AIRO (the Italian Association for Operations Research). The book includes contributions in the fields of operations research, optimization, problem solving, decision making and their applications in the most diverse domains. Moreover, a special focus is set on the challenging theme Operations Research: inclusion and equity. The work offers 30 contributions, covering a wide spectrum of methodologies and applications. Specifically, they feature the following topics: (i) Variational Inequalities, Equilibria and Games, (ii) Optimization and Machine Learning, (iii) Global Optimization, (iv) Optimization under Uncertainty, (v) Combinatorial Optimization, (vi) Transportation and Mobility, (vii) Health Care Management, and (viii) Applications. This book is primarily addressed to researchers and PhD students of the operations research community. However, due to its interdisciplinary content, it will be of high interest for other closely related research communities.

Logistics and transportation are a complex set of entities and systems interconnected by many physical, financial, and information flows, and, as with all systems, there are optimization and planning issues. In addition, they are subject to economic, social, and especially environmental pressures with the need to reduce energy consumption and greenhouse gas emissions. There is a need for original research to address these issues. Transport and Logistics Planning and Optimization addresses selected transportation and logistics problems at the strategic, tactical, and operational levels in a multidisciplinary approach, not only from a technological perspective but also from a social science perspective. Covering key topics such as supply chain, urban transportation, artificial intelligence, and computer science, this premier reference source is ideal for policymakers, industry professionals, researchers, academicians, scholars, instructors, and students.

This is a collection of state-of-the-art surveys on topics at the interface between transportation modeling and operations research given by leading international experts. Based on contributions to a NATO workshop, the surveys are up-to-date and rigorous presentations or applications of quantitative methods in the area. The subjects covered include dynamic traffic simulation techniques and dynamic routing in congested networks, operation and control of traffic management tools, optimized transportation data collection, and vehicle routing problems.

The scientific monograph of a survey kind presented to the reader's attention deals with fundamental ideas and basic schemes of optimization methods that can be effectively used for solving strategic planning and operations manage ment problems related, in particular, to transportation. This monograph is an English translation of a considerable part of the author's book with a similar title that was published in Russian in 1992. The material of the monograph embraces methods of linear and nonlinear programming; nonsmooth and nonconvex optimization; integer programming, solving problems on graphs, and solving problems with mixed variables; rout ing, scheduling, solving network flow problems, and solving the transportation problem; stochastic programming, multicriteria optimization, game theory, and optimization on fuzzy sets and under fuzzy goals; optimal control of systems described by ordinary differential equations, partial differential equations, gen eralized differential equations (differential inclusions), and functional equations with a variable that can assume only discrete values; and some other methods that are based on or adjoin to the listed ones.

​As urban congestion continues to be an ever increasing problem, routing in these settings has become an important area of operations research. This monograph provides cutting-edge research, utilizing the recent advances in technology, to quantify the value of dynamic, time-dependent information for advanced vehicle routing in city logistics. The methodology of traffic data collection is enhanced by GPS based data collection, resulting in a comprehensive number of travel time records. Data Mining is also applied to derive dynamic information models as required by time-dependent optimization. Finally, well-known approaches of vehicle routing are adapted in order to handle dynamic information models. This book interweaves the usually distinct areas of traffic data collection, information retrieval and time-dependent optimization by an integrated methodological approach, which refers to synergies of Data Mining and Operations Research techniques by example of city logistics applications. These procedures will help improve the reliability of logistics services in congested urban areas.​

​As urban congestion continues to be an ever increasing problem, routing in these settings has become an important area of operations research. This monograph provides cutting-edge research, utilizing the recent advances in technology, to quantify the value of dynamic, time-dependent information for advanced vehicle routing in city logistics. The methodology of traffic data collection is enhanced by GPS based data collection, resulting in a comprehensive number of travel time records. Data Mining is also applied to derive dynamic information models as required by time-dependent optimization. Finally, well-known approaches of vehicle routing are adapted in order to handle dynamic information models. This book interweaves the usually distinct areas of traffic data collection, information retrieval and time-dependent optimization by an integrated methodological approach, which refers to synergies of Data Mining and Operations Research techniques by example of city logistics applications. These procedures will help improve the reliability of logistics services in congested urban areas.​