A Genetic Algorithm with Modified Crossover Operator for a Two-Agent Scheduling Problem

The problem of scheduling with multi agent has been studied for more than one decade and significant advances have been made over the years. However, most work has paid more attention to the condition that machines are available during planning horizon. Motivated by the observations, this paper studies a two-agent scheduling model with multiple availability constraint. Each agent aims at minimizing a function which depends only on the completion times of its jobs. The problem is to find a schedule that minimizes the objective function of one agent, subject to the objective function of the other agent does not exceed a given threshold Q. some new dominance properties for this problem percent and next, using these properties, we develop a genetic algorithm with modified crossover for the problem. Computational results are also presented to determine the performance of the proposed genetic algorithms.