The book is devoted to structural issues, algorithms, and applications of resource allocation problems in project management. Special emphasis is given to a unifying framework within which a large variety of project scheduling problems can be treated. Those problems involve general temporal constraints among project activities, different types of scarce resources, and a broad class of regular and nonregular objective functions ranging from time-based and financial to resource levelling functions. The diversity of the models proposed allows for covering many features arising in scheduling applications beyond the field of project management such as short-term production planning in the manufacturing or process industries.

This multi-author volume, containing contributions from international experts in the field, presents recent developments in project scheduling for both theory and practice. It is organized in three parts: I. Basic deterministic models; II. Special deterministic models; III. Stochastic models. A variety of approaches is presented dealing with multiple-category resource constraints, different mathematical models of activities, and various project performance measures in single and multiobjective formulation. Exact and heuristic algorithms are presented for both deterministic and stochastic project description.The volume will be of special interest to scientists, students, decision makers, executive managers, consultants and practitioners involved in systems management or operations research, in particular in business, engineering, and finance, but also in other areas of pure and applied sciences.

A well-managed project results in efficient scheduling of the interrelated components of work tasks, resources, stakeholders and budgets plans. The goal is for project managers to be able to generate an initial schedule at an early stage of product development. Due to complex product development, uncertainties and variabilities exists during manufacturing process. Variable processing times may lead to multiple critical paths within the system. Based on the real world demands of project managers two objectives are considered: Identification of multiple critical paths within the system and minimize completion time of the activity by optimal resource allocation. To solve this problem, a mixed integer linear programming model (MILP) is proposed. The Multiple critical path scheduling approach (MCPSA) is developed to identify multiple critical paths dominant in a system. A criticality index is used as performance metric to measure the intensity of the critical path in comparison to the project completion time. An interface of MS- Project with a simulation software (@RISK) is used to obtain the results. An application of two auger screws used in extrusion molding machines from a leading manufacturer in Kansas is used to illustrate the case study models and the MCPSA algorithm.

We consider large-scale, network-based, resource allocation problems under uncertainty, with specific focus on the class of problems referred to as multi-commodity flow problems with time-windows. These problems are at the core of many network-based resource allocation problems. Inherent data uncertainty in the problem guarantees that deterministic optimal solutions are rarely, if ever, executed. Our work examines methods of proactive planning, that is, robust plan generation to protect against future uncertainty. By modeling uncertainties in data corresponding to service times, resource availability, supplies and demands, we can generate solutions that are more robust operationally, that is, more likely to be executed or easier to repair when disrupted. The challenges are the following: approaches to achieve robustness 1) can be extremely problem-specific and not general; 2) suffer from issues of tractability; or 3) have unrealistic data requirements. We propose in this work a modeling and algorithmic framework that addresses the above challenges.

Real-Time Management of Resource Allocation Systems focuses on the problem of managing the resource allocation taking place within the operational context of many contemporary technological applications, including flexibly automated production systems, automated railway and/or monorail transportation systems, electronic workflow management systems, and business transaction supporting systems. A distinct trait of all these applications is that they limit the role of the human element to remote high-level supervision, while placing the burden of the real-time monitoring and coordination of the ongoing activity upon a computerized control system. Hence, any applicable control paradigm must address not only the issues of throughput maximization, work-in-process inventory reduction, and delay and cost minimization, that have been the typical concerns for past studies on resource allocation, but it must also guarantee the operational correctness and the behavioral consistency of the underlying automated system. The resulting problem is rather novel for the developers of these systems, since, in the past, many of its facets were left to the jurisdiction of the present human intelligence. It is also complex, due to the high levels of choice – otherwise known as flexibility – inherent in the operation of these environments.

This volume features the proceedings of the 14th ISPE Conference on Concurrent Engineering, held in São José dos Campos, São Paulo, Brazil, on the 16th – 20th of July 2007. It highlights the application of concurrent engineering to the development of complex systems.