Pareto max-min ant system algorithm and its application to hot rolling batch planning problem
Pareto最大最小蚂蚁算法及其在热轧批量计划优化中的应用

A Pareto concept-based max-min ant system algorithm for the bi-objective traveling salesman problem is proposed. By modifying the state transition rule, pheromone updating rule and the local search rule; as well as employing an adaptive-grid based diversity maintenance approach and the pheromone trail smoothing mechanism, we find the approximate Pareto front which is uniformly distributed on the objective space. Simulation on 6 benchmark functions and application to a hot rolling batch planning problem indicate that the proposed algorithm has desirable performance and practicability.