This book surveys the current state-of-the-art in operations research. The book summarizes the current developments and theoretical achievements in the field, including project uncertainty and grid resource management. It further covers the range of the key models in the field, including deterministic, probabilistic, single- and multi-mode, single- and multi-objective, and a general model on discrete-continuous resources.

Résumé

Operations Research began with the mathematical scheduling of a massive projectlogistically supplying Europe with military equipment and goods during the WWII. Today project scheduling research continues growing in a variety of its theoretical models, in its magnitude and application. As the world becomes more interrelated and complex, the wider its research is applied to an increasing number of project scheduling problems.

Project Scheduling: Surveying the State-of-the-Art surveys the current state-of-the-art in operations research with chapters written by the respective leading experts on each topic. It covers the range of the key models in the field, including deterministic, probabilistic, single- and multi-mode, single- and multi-objective, and a general model on discrete-continuous resources. Recent solution algorithms are systematical examined. The book summarize sthe current developments and theoretical achievements in the field, including project uncertainty and grid resource management.

Contenu
Models.- A Practical and Accurate Alternative to PERT.- Proactive-Reactive Project Scheduling Trade-Offs and Procedures.- Resource Constrained Project Scheduling Models under Random Disturbances.- Due Dates and RCPSP.- RCPS with Variable Intensity Activities and Feeding Precedence Constraints.- Modelling Setup Times in Project Scheduling.- Algorithms.- Lower Bounds for Resource Constrained Project Scheduling Problem.- Justification Technique Generalizations.- A Metaheuristic Approach to the Resource Constrained Project Scheduling with Variable Activity Durations and Convex Cost Functions.- A Hybrid Genetic Algorithm Based on Intelligent Encoding for Project Scheduling.- Population Learning Algorithm for the Resource-Constrained Project Scheduling.- Resource Constrained Project Scheduling: a Hybrid Neural Approach.- Applications.- Selection and Scheduling of Pharmaceutical Research Projects.- Grid Multicriteria Job Scheduling with Resource Reservation and Prediction Mechanisms.- Resource-Constrained Project Scheduling with Time Windows.- CP-Based Decision Support for Project Driven Manufacturing.