Project Scheduling with Time Windows and Scarce Resources


Book Description

A survey of the state of the art of deterministic resource-constrained project scheduling with time windows. General temporal constraints and several different types of limited resources are considered. A large variety of time-based, financial, and resource-based objectives - important in practice - are studied. A thorough structural analysis of the feasible region of project scheduling problems and a classification and detailed investigation of objective functions are performed, which can be exploited for developing efficient exact and heuristic solution methods. New interesting applications of project scheduling to production and operations management as well as investment projects are discussed in the second edition.







Project Scheduling with Time Windows and Scarce Resources


Book Description

A survey of the state of the art of deterministic resource-constrained project scheduling with time windows. General temporal constraints and several different types of limited resources are considered. A large variety of time-based, financial, and resource-based objectives - important in practice - are studied. A thorough structural analysis of the feasible region of project scheduling problems and a classification and detailed investigation of objective functions are performed, which can be exploited for developing efficient exact and heuristic solution methods. New interesting applications of project scheduling to production and operations management as well as investment projects are discussed in the second edition.







Project Scheduling with Time Windows


Book Description

Project Scheduling is concerned with the allocation of scarce resources over time. The rich optimisation models with time windows that are treated in this book cover a multitude of practical decision problems arising in diverse application areas such as construction engineering or make-to-order production planning. The book shows how Constraint Propagation techniques from Artificial Intelligence can be successfully combined with Operations Research methods for developing powerful exact and heuristic solution algorithms for a very general class of scheduling problems. Example applications demonstrate the effectiveness of the approach.




Resource-Constrained Project Scheduling


Book Description

This title presents a large variety of models and algorithms dedicated to the resource-constrained project scheduling problem (RCPSP), which aims at scheduling at minimal duration a set of activities subject to precedence constraints and limited resource availabilities. In the first part, the standard variant of RCPSP is presented and analyzed as a combinatorial optimization problem. Constraint programming and integer linear programming formulations are given. Relaxations based on these formulations and also on related scheduling problems are presented. Exact methods and heuristics are surveyed. Computational experiments, aiming at providing an empirical insight on the difficulty of the problem, are provided. The second part of the book focuses on several other variants of the RCPSP and on their solution methods. Each variant takes account of real-life characteristics which are not considered in the standard version, such as possible interruptions of activities, production and consumption of resources, cost-based approaches and uncertainty considerations. The last part presents industrial case studies where the RCPSP plays a central part. Applications are presented in various domains such as assembly shop and rolling ingots production scheduling, project management in information technology companies and instruction scheduling for VLIW processor architectures.




Project Scheduling


Book Description

Project scheduling problems are, generally speaking, the problems of allocating scarce resources over time to perform a given set of activities. The resources are nothing other than the arbitrary means which activities complete for. Also the activities can have a variety of interpretations. Thus, project scheduling problems appear in a large spectrum of real-world situations, and, in consequence, they have been intensively studied for almost fourty years. Almost a decade has passed since the multi-author monograph: R. Slowinski, 1. W~glarz (eds. ), Advances in Project Scheduling, Elsevier, 1989, summarizing the state-of-the-art across project scheduling problems, was published. Since then, considerable progress has been made in all directions of modelling and finding solutions to these problems. Thus, the proposal by Professor Frederick S. Hillier to edit a handbook which reports on the recent advances in the field came at an exceptionally good time and motivated me to accept the challenge. Fortunately, almost all leading experts in the field have accepted my invitation and presented their completely new advances often combined with expository surveys. Thanks to them, the handbook stands a good chance of becoming a key reference point on the current state-of-the-art in project scheduling, as well as on new directions in the area. The contents are divided into four parts. The first one, dealing with classical models -exact algorithms, is preceded by a proposition of the classification scheme for scheduling problems.




Project Scheduling under Limited Resources


Book Description

Approaches to project scheduling under resource constraints are discussed in this book. After an overview of different models, it deals with exact and heuristic scheduling algorithms. The focus is on the development of new algorithms. Computational experiments demonstrate the efficiency of the new heuristics. Finally, it is shown how the models and methods discussed here can be applied to projects in research and development as well as market research.




Evolutionary Computation in Combinatorial Optimization


Book Description

This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2007, held in Valencia, Spain in April 2007. The 21 revised full papers presented were carefully reviewed and selected from 81 submissions. The papers cover evolutionary algorithms as well as various other metaheuristics, like scatter search, tabu search, memetic algorithms, variable neighborhood search, greedy randomized adaptive search procedures, ant colony optimization, and particle swarm optimization algorithms. The papers are specifically dedicat.