A case study of scheduling storage tanks using a hybrid genetic algorithm

This paper proposes the application of a hybrid genetic algorithm (GA) for scheduling storage tanks. The proposed approach integrates GAs and heuristi c rule-based techniques, decomposing the complex mixed-integer optimization problem into integer and real-number subproblems. The GA string considers the integer problem and the heuristic approach solves the real-number probl ems within the GA framework. The algorithm is demonstrated for three test s cenarios of a water treatment facility at a port and has been found to be r obust and to give a significantly better schedule than those generated usin g a random search and a heuristic-based approach.