Papers by Keyword: RCPSP

Abstract: A resource-constrained project scheduling problem with stochastic resource-dependent activity durations is presented in this paper,and the two-point method is employed to simulate the uncertain property.Furthermore a genetic algorithm combined with this method is provided to solve the problem. Compared with the results from the genetic with Monte Carlo simulation, the proposed method is verified to be effective and more efficient.

Abstract: The critical chain project management theory(CCPM) combining the critical chain technology and resource-constrained project scheduling problem (RCPSP) is an important innovation of project control methods, and it’s widely used to optimize the project duration recently. In this paper the theory presented is applied to the maintenance period arrangements of power plant electrical equipment, and a mathematical model of optimizing the maintenance period is established. Then an improved heuristic algorithm is designed and used to establish equipment maintenance precedence network. On this basis, a new identification method of maintenance network based on critical chain is proposed. Finally, it’s verified with a numerical example that the method proposed can effectively shorten the maintenance period of power plant electrical equipment.

Abstract: This paper presents a cat swarm optimization (CSO)-based method for resource constrained project scheduling problem (RCPSP). The CSO simulates the behavior of cats in two sub-models and potential solution to the RCPSP is presented by the multidimensional positions of cats. CSO-based scheme for the RCPSP has three main stages: first randomly initialize the parameters of cats, then update the position in iteration and calculate the fitness through serial SGS method, finally terminate the process if the condition is satisfied. Compared to the other widely used heuristic methods, CSO is easy to understand and to implement. The adoption of CSO in solving RCPSP indicates the universality of CSO in solving operational problems. When solving RCPSP, some refinement of original CSO are made. The performance of the proposed algorithm is compared against a set of heuristic and meta-heuristic methods, and it is tested on standard problem sets called PSPLIB which is freely available on the Internet. The empirical results show that CSO has an average good performance among the other compared methods.

Abstract: The resource-constrained project scheduling is an important problem for enterprise resource planning. We herein propose a differential evolution with scatter search structure (named by DESS hereinafter) to tackle resource-constrained project scheduling problem. DESS follows the scatter search structure but uses differential evolution (DE) to generate new solutions of SS, and applies 3-opt local search algorithm as the improvement method of SS to transform each trial solution into enhanced trial solution. The proposed DESS is compared with the state-of-the-art algorithms on a set of standard problems available in the literature. The experimental results validate the effectiveness of DESS.

Abstract: Globalisation in large engineering, procurement and construction companies has lead in many cases to the establishment of a number of global centres for activities such as process design, detail design, procurement and fabrication. A company with a number of such resources then faces the problem of maintaining a high percentage utilisation in each of these resource locations, multiple projects need to be processed through each of these offices and which project is handled by which office is generally more reliant on available capacity than geography, particularly in the case of engineering centres. This paper considers this problem as an extension of the well studied Resource Constrained Project Scheduling Problem (RCPSP) and utilises a modified form of our existing genetic algorithm to optimise the utilisation of multiple resource locations when scheduling multiple projects. The unique aspect of this genetic algorithm implementation is its use of stochastic resource assignments to simulate the assignment of certain of the project activities to different global facilities. The stochastic resource assignment is processed as an extension to the main chromosome and is therefore optimised along with the scheduling sequence.