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

An exact depth-first algorithm for the pallet loading problem

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

‘Buy online and pick up in-store’: Implications for the store inventory

This paper presents an agent-based model to select an investment portfolio with a restriction on the number of stocks in it. Daily movements of all the stocks in the market for the past few years are assumed to be available. The scheme deploys a federally structured consortium of agents in the stock market at the start of the historical period. Each agent starts with a pseudorandom portfolio and follows individual investment strategies as it walks through the past data. The agents are designed to emulate some of the characteristics of human investors-adjusting the weights of the stocks based on its own attitude toward risk, occasionally dropping and adding stocks to the portfolio, etc. Periodically, the agents share information about their performances and can switch portfolios. A final cardinality constrained portfolio is constructed by consolidating individual portfolios arrived at by the agents working on the historical data of the stocks. When tested in real markets of the U.K. and Japan, the model suggested portfolios that were quite competitive to, and frequently better than, the portfolios suggested by the mean-variance models.

Cooperative Search Using Agents for Cardinality Constrained Portfolio Selection Problem

As software houses align themselves to serve clients operating in rapidly changing business environments, they start putting more emphasis on increasing their agility. However as a precursor to this, there is a need within an organization to measure and monitor its agility. The clients also would be interested to know the level of agility of their vendors. While the need for an effective metric is well established, the subjective nature of the parameters involved, and the need for some degree of generality makes the task of assessing agility a difficult one. This paper is an attempt to arrive at a quantifiable, scalable framework to measure the same. Apart from giving a framework which can be used to assess the agility of a company, this paper indicates how a detailed sensitivity analysis can be done with respect to the parameters that define agility.

Subir Bhattacharya

Papers

An exact depth-first algorithm for the pallet loading problem

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

‘Buy online and pick up in-store’: Implications for the store inventory

Cooperative Search Using Agents for Cardinality Constrained Portfolio Selection Problem

Towards a Framework for Assessing Agility