Forward-backward Improvement for Genetic Algorithm Based Optimization of Resource Constrained Scheduling Problem
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Project scheduling with limited resources is a challenging management problem that is of immense importance to both practitioners and researchers. This problem is known to be NP-hard even under the simplifying assumptions of single renewable resource constraint, its constant avai
This work describes a genetic algorithm approach to resource-constrained scheduling using a direct, time-based representation. Whereas traditional solution methods are typically sequencebased, this representation encodes schedule information as a dual array of relative delay time
In this paper, an improved genetic algorithm is designed to solve the above multiobjective optimization problem for scheduling of college English courses. Firstly, a variable-length decimal coding scheme satisfying same course that can be scheduled at different times, classrooms,