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Geometric Modelling, Numerical Simulation, and Optimization:
This edited volume addresses the importance of mathematics for industry and society by presenting highlights from contract research at the Department of Applied Mathematics at SINTEF, the largest independent research organization in Scandinavia. Examples range from computer-aided geometric design, via general purpose computing on graphics cards, to reservoir simulation for enhanced oil recovery. Contributions are written in a tutorial style.
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 6th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2006, held in Budapest, Hungary in April 2006. The 24 revised full papers presented were carefully reviewed and selected from 77 submissions. The papers include coverage of evolutionary algorithms as well as various other metaheuristics, like scatter search, tabu search, and memetic algorithms.
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009, held in Tübingen, Germany, in April 2009. The 21 revised full papers presented were carefully reviewed and selected from 53 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms and ant colony optimization.
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 23rd European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2023, held as part of Evo*2023, in Brno, Czech Republic in April 2023, co-located with the Evo*2023 events: EvoMUSART, EvoApplications, and EuroGP. The 15 revised full papers presented in this book were carefully reviewed and selected from 32 submissions. They present recent theoretical and experimental advances in combinatorial optimization, evolutionary algorithms, and related research fields.
Computational Logistics
This book constitutes the refereed proceedings of the 7th International Conference on Computational Logistics, ICCL 2016, held in Lisbon, Portugal, in September 2016. The 29 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: container terminals and maritime transportation; intermodal transport; location and routing; (general) logistics and supply chain management.
Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated an...
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2010, held in Instanbul, Turkey, in April 2010. The 24 revised full papers presented were carefully reviewed an selected from 69 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy radomized adaptive search procedures, estimation of distribution algorithms and ant colony opitmization.
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 16th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo*2015 events EuroGP, EvoMUSART and EvoApplications. The 17 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers cover methodology, applications and theoretical studies. The methods included evolutionary and memetic algorithms, variable neighborhood search, particle swarm optimization, hyperheuristics, mat-heuristic and other adaptive approaches. Applications included both traditional domains, such as graph coloring, vehicle routing, the longest common subsequence problem, the quadratic assignment problem; and new(er) domains such as the traveling thief problem, web service location, and finding short addition chains. The theoretical studies involved fitness landscape analysis, local search and recombination operator analysis, and the big valley search space hypothesis. The consideration of multiple objectives, dynamic and noisy environments was also present in a number of articles.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Learning and Intelligent Optimization
This volume collects the accepted papers presented at the Learning and Intelligent OptimizatioN conference (LION 2007 II) held December 8–12, 2007, in Trento, Italy. The motivation for the meeting is related to the current explosion in the number and variety of heuristic algorithms for hard optimization problems, which raises - merous interesting and challenging issues. Practitioners are confronted with the b- den of selecting the most appropriate method, in many cases through an expensive algorithm configuration and parameter-tuning process, and subject to a steep learning curve. Scientists seek theoretical insights and demand a sound experimental meth- ology for evaluating algorithms and...
