http://web.nchu.edu.tw/pweb/users/arborfish/lesson/8682.pdf

A survey of variants and extensions of the resource-constrained project scheduling problem

There have been many survey papers in the area of project scheduling in recent years. These papers have primarily emphasized modeling and algorithmic contributions for specific classes of project scheduling problems, such as net present value (NPV) maximization and makespan minimization, with and without resource constraints. Paralleling these developments has been the research in the area of project scheduling decision support, with its emphasis on data sets, data generation methods, and so on, that are essential to benchmark, evaluate, and compare the new models, algorithms and heuristic techniques. These investigations have extended the frontiers of research and application in all areas of project scheduling and management. In this paper, we survey the vast literature in this area with a perspective that integrates models, data, and optimal and heuristic algorithms, for the major classes of project scheduling problems. We also include recent surveys that have compared commercial project scheduling systems. Finally, we present an overview of web-based decision support systems and discuss the potential of this technology in enabling and facilitating researchers and practitioners in identifying new areas of inquiry and application.

http://web.nchu.edu.tw/pweb/users/arborfish/lesson/8681.pdf

An integrated survey of deterministic project scheduling

Branch-and-bound algorithms

Genetic algorithms have been applied to many different optimization problems and they are one of the most promising metaheuristics However, there are few published studies concerning the design of efficient genetic algorithms for resource allocation in project scheduling In this work we present a robust genetic algorithm for the single-mode resource constrained project scheduling problem We propose a new representation for the solutions, based on the standard activity list representation and develop new crossover techniques with good performance in a wide sample of projects Through an extensive computational experiment, using standard sets of project instances, we evaluate our genetic algorithm and demonstrate that our approach outperforms the best algorithms appearing in the literature

A Robust Genetic Algorithm for Resource Allocation in Project Scheduling

The multiple resource constrained project scheduling problem : A breadth-first approach

To examine sex bias in occupational prestige, 250 male and 250 female undergraduate and graduate students in Bombay were asked to rate the respectability of 16 occupations, each with male and female occupants (e.g., a male scientist, a female scientists, etc.). Thus, the study had a 2 (subject's sex) × 2 (occupant's gender) × 16 (occupations) mixed design, with occupant's gender and occupations as within-subjects factors. All of the main and interaction ANOVA effects were significant. The findings clearly supported the primary hypothesis that both male and female subjects would show a sex bias in favor of the male occupant in cases of high prestige occupations.

Terence Nazareth

Papers

The multiple resource constrained project scheduling problem : A breadth-first approach

Occupational Prestige as a Function of Occupant's Gender