Invited Paper -- Metaheuristic Agent Processes (MAPS) -- Tutorial Paper -- GRASP with Path-Relinking: Recent Advances and Applications -- Papers on Problem Solving -- A Tabu Search Heuristic for a University Timetabling Problem -- An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-Heuristic -- Validation and Optimization of an Elevator Simulation Model with Modern Search Heuristics -- Multi-Objective Hyper-Heuristic Approaches for Space Allocation and Timetabling -- Theory and Practice of the Minimum Shift Design Problem -- Local Search Algorithms for the Two-Dimensional Cutting Stock Problem with a Given Number of Different Patterns -- A Generic Object-Oriented Tabu Search Framework -- Bi-Objective Sequencing of Cutting Patterns -- Metaheuristics Approach for Rule Acquisition in Flexible Shop Scheduling Problems -- Predicting Colorectal Cancer Recurrence: A Hybrid Neural Networks-Based Approach -- A Constructive Genetic Approach to Point-Feature Cartographic Label Placement -- Papers on Methodologies -- Parallel Strategies for Grasp with Path-Relinking -- Speeding Up Local Search Neighborhood Evaluation for A Multi-Dimensional Knapsack Problem -- Computationally Difficult Instances for the Uncapacitated Facility Location Problem -- Consistent Neighbourhood in a Tabu Search -- Constraint Oriented Neighbourhoods — A New Search Strategy in Metaheuristics.Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field. Included are an invited paper by F. Glover and G. Kochenberger, which discusses the concept of Metaheuristic agent processes, and a tutorial paper by M.G.C. Resende and C.C. Ribeiro discussing GRASP with path-relinking. Other papers discuss problem-solving approaches to timetabling, automated planograms, elevators, space allocation, shift design, cutting stock, flexible shop scheduling, colorectal cancer and cartography. A final group of methodology papers clarify various aspects of Metaheuristics from the computational view point.