Abstract
Due to the development of management idea and the scarcity of some resources, the lean management has become the necessary request to implement effective control of resource constrained project. Resource constrained project scheduling is the significant guarantee to attain the lean management. The resource constrained project scheduling problem (RCPSP), with the objective of minimizing project duration and with the precedence relations described by an activity-on-arrow (AOA) network, is formulated as a combination optimization problem and solved using the priority-based genetic algorithm (GA). The activity priorities are represented by chromosome and serial scheduling scheme (SSS) and parallel scheduling scheme (PSS) are developed and utilized to transform chromosome-represented priorities to an active schedule subject to the logic and resource constraints so that project duration corresponding to each chromosome can be evaluated. The overall framework of the GA for the RCPSP is developed and the basic components of the algorithm are designed. Simulation is provided so as to investigate the performance of the priority-based GA with SSS and PSS as decoding method, respectively. The optimal solution to a small-sized resource constrained benchmark instance is scheduled to find the shortest project duration. Comparative simulation results demonstrate not only the effectiveness and efficiency of GA with SSS or PSS as decoding methods in solution to RCPSP with precedence relation of activities diagramed as an AOA network but also the effect of different evolution parameter settings on solution quality of the problem.
Highlights
Due to the development of management idea and the scarcity of resources, the importance of lean management has been gradually recognized
Since resource constrained project schedule problem (RCPSP) is formulated as a minimization problem, and the roulette wheel selection is a fitness-proportional selection, a transformation is utilized to map the natural objective value into a fitness value to ensure the individual of lower objective value has bigger selection probability
The transformation of objective value Tp corresponding to chromosome c into a fitness value is implemented by an absolute fitness function as shown in (6)
Summary
Due to the development of management idea and the scarcity of resources, the importance of lean management has been gradually recognized. The objective of RCPSP is to properly schedule dependent activities over time such that the task duration is minimized while the precedence and resource constraints have to be met. Jiancheng Wang: Optimization and Simulation of Resource Constrained Scheduling Problem Using Genetic Algorithm branch and bound algorithms, and Gavish and Pirkul [2] used dynamic programming. This work is focused on a genetic algorithm based metaheuristic approach with both serial scheduling scheme (SSS) and parallel scheduling scheme (PSS) as schedule generation scheme (SGS) to assist the resource constrained project scheduling. Simulation results demonstrate the solution quality and efficiency of RCPSP with moderate size is rather satisfactory. The rest of this paper is organized as follows: in Section 2 RCPSP is formulated as a combination optimization problem, in Section 3 the framework and basic components of genetic algorithm are developed and designed.
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