A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives -- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem -- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search -- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling -- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When -- Decomposing SAT Instances with Pseudo Backbones -- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control -- Estimation of Distribution Algorithms for the Firefighter Problem -- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows -- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO -- Optimizing Charging Station Locations for Electric Car-Sharing Systems -- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier -- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants -- The Weighted Independent Domination Problem: ILP Model and Algorithmic .

This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial optimization.