2 research outputs found
An improved ant algorithm for Multi-mode Resource Constrained Project Scheduling Problem
Many real-world scheduling problems can be modeled as Multi-mode Resource Constrained
Project Scheduling Problems (MRCPSP). However, the MRCPSP is a strong NP-hard problem and
very difficult to be solved. The purpose of this research is to investigate a more
efficient alternative based on ant algorithm to solve MRCPSP. To enhance the generality
along with efficiency of the algorithm, the rule pool is designed to manage numerous
priority rules for MRCPSP. Each ant is provided with an independent thread and endowed
with the learning ability to dynamically select the excellent priority rules. In addition,
all the ants in the ant algorithm have the prejudgment ability to avoid infeasible routes
based on the branch and bound method. The algorithm is tested on the well-known benchmark
instances in PSPLIB. The computational results validate the effectiveness of the proposed
algorithm