This book constitutes the refereed proceedings of the 17th International Conference on Principles and Practice of Constraint Programming, CP 2011, held in Perugia, Italy, September 12-16, 2011. The 51 revised full papers and 7 short papers presented together with three invited talks were carefully reviewed and selected from 159 submissions. The papers are organized in topical sections on algorithms, environments, languages, models and systems, applications such as decision making, resource allocation and agreement technologies.

This book constitutes the refereed proceedings of the Second International Workshop on Experimental and Efficient Algorithms, WEA 2003, held in Ascona, Switzerland in May 2003. The 19 revised full papers presented together with 3 invited contributions were carefully reviewed and selected from 40 submissions. The focus of the volume is on applications of efficient algorithms for combinatorial problems.

Column Generation is an insightful overview of the state of the art in integer programming column generation and its many applications. The volume begins with "A Primer in Column Generation" which outlines the theory and ideas necessary to solve large-scale practical problems, illustrated with a variety of examples. Other chapters follow this introduction on "Shortest Path Problems with Resource Constraints," "Vehicle Routing Problem with Time Window," "Branch-and-Price Heuristics," "Cutting Stock Problems," each dealing with methodological aspects of the field. Three chapters deal with transportation applications: "Large-scale Models in the Airline Industry," "Robust Inventory Ship Routing by Column Generation," and "Ship Scheduling with Recurring Visits and Visit Separation Requirements." Production is the focus of another three chapters: "Combining Column Generation and Lagrangian Relaxation," "Dantzig-Wolfe Decomposition for Job Shop Scheduling," and "Applying Column Generation to Machine Scheduling." The final chapter by François Vanderbeck, "Implementing Mixed Integer Column Generation," reviews how to set-up the Dantzig-Wolfe reformulation, adapt standard MIP techniques to the column generation context (branching, preprocessing, primal heuristics), and deal with specific column generation issues (initialization, stabilization, column management strategies).

ABSTRACT: In the world of optimization, network optimization problems are considered fundamental to the practice. The work presented here focuses on the similarity constrained k shortest paths problem (SCKSPP) its formulation, and subsequent analysis. The formulation addresses several deficiencies which are present in prior works, and the analysis focuses on addressing major topics of feasibility and optimality which are not present in prior works. SCKSPP focuses around finding k simple paths from source to sink nodes while maintaining a pairwise dissimilarity. The purpose of this paper is to develop an underlying theory behind the SCKSPP to guide the development of an efficient solution method. The work itself is entirely theoretical; we give properties which use graph connectivity to describe the existence of feasible solutions, we demonstrate how objective function behavior affects uniqueness of the optimal solution, as well as other properties regarding feasibility and optimality. Furthermore, we show how specific graph structures allow smaller less computationally intensive problems to be solved, and then extrapolated to form optimal solutions of the larger problems. We also give several examples of similarity measures that incorporate context-specific constraints into already existing similarity constraints.

This book constitutes the refereed proceedings of the Third International Workshop on Algorithm Engineering, WAE'99, held in London, UK in July 1999. The 24 revised full papers presented were carefully reviewed and selected from a total of 46 submissions. The papers present original research results in all aspects of algorithm engineering including implementation, experimental testing, fine-tuning of discrete algorithms, development of repositories of software, methodological issues such as standards for empirical research on algorithms and data structures, and issues in the process of converting user requirements into efficient algorithmic solutions and implementations.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

This book constitutes the refereed proceedings of the 8th Annual European Symposium on Algorithms, ESA 2000, held in Saarbrcken, Germany in September 2000. The 39 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the book. Among the topics addressed are parallelism, distributed systems, approximation, combinatorial optimization, computational biology, computational geometry, external-memory algorithms, graph algorithms, network algorithms, online algorithms, data compression, symbolic computation, pattern matching, and randomized algorithms.