Constraint

Packed with new material and research, this second edition of George Friedman’s bestselling Constraint Theory remains an invaluable reference for all engineers, mathematicians, and managers concerned with modeling. As in the first edition, this text analyzes the way Constraint Theory employs bipartite graphs and presents the process of locating the “kernel of constraint” trillions of times faster than brute-force approaches, determining model consistency and computational allowability.

Differing from other books on the subject, this one uses the framework of constraint databases to provide a natural and powerful generalization of relational databases. An important theme running through the text is showing how relational databases can smoothly develop into constraint databases, without sacrificing any of the benefits of relational databases whilst gaining new advantages. Peter Revesz begins by discussing data models and how queries may be addressed to them. From here, he develops the theory of relational and constraint databases, including Datalog and the relational calculus, concluding with three sample constraint database systems – DISCO, DINGO, and RATHER. Advanced undergraduates and graduates in computer science will find this a clear introduction to the subject, while professionals and researchers will appreciate this novel perspective on their subject.

An efficient and adequate constraint-handling technique is a key element in the design of competitive evolutionary algorithms to solve complex optimization problems. This edited book presents a collection of recent advances in nature-inspired techniques for constrained numerical optimization. The book covers six main topics: swarm-intelligence-based approaches, studies in differential evolution, evolutionary multiobjective constrained optimization, hybrid approaches, real-world applications and the recent use of the artificial immune system in constrained optimization. Within the chapters, the reader will find different studies about specialized subjects, such as: special mechanisms to focus the search on the boundaries of the feasible region, the relevance of infeasible solutions in the search process, parameter control in constrained optimization, the combination of mathematical programming techniques and evolutionary algorithms in constrained search spaces and the adaptation of novel nature-inspired algorithms for numerical optimization with constraints.

This volume LNCS 12735 constitutes the papers of the 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, which was held in Vienna, Austria, in 2021. Due to the COVID-19 pandemic the conference was held online.