Non-dominated archiving multi-colony ant algorithm for multi-objective optimization: Application to multi-purpose reservoir operation

Abstract

Multi-objective optimization using heuristic methods has been established as a 
subdiscipline that combines the fields of heuristic computation and classical 
multiple criteria decision making. This article presents the Non-dominated 
Archiving Ant Colony Optimization (NA-ACO), which benefits from the concept 
of a multi-colony ant algorithm and incorporates a new information-exchange 
policy. In the proposed information-exchange policy, after a given number of 
iterations, different colonies exchange information on the assigned objective, 
resulting in a set of non-dominated solutions. The non-dominated solutions are 
moved into an offline archive for further pheromone updating. Performance of 
the NA-ACO is tested employing two well-known mathematical multi-objective 
benchmark problems. The results are promising and compare well with those of 
well-known NSGA-II algorithms used in real-world multi-objective-optimization 
problems. In addition, the optimization of reservoir operating policy with multiple 
objectives (i.e. flood control, hydropower generation and irrigation water supply) 
is considered and the associated Pareto front generated.