In this paper we introduce ACOP, a novel ACO algorithmfor solving permutation based optimization problems. The main noveltyis in how ACOP ants construct a permutation by navigating the spaceof partial orders and considering precedence relations as solution components.Indeed, a permutation is built up by iteratively adding precedencerelations to a partial order of items until it becomes a total order, thus thecorresponding permutation is obtained. The pheromone model and theheuristic function assign desirability values to precedence relations. AnACOP implementation for the Linear Ordering Problem (LOP) is proposed.Experiments have been held on a large set of widely adopted LOPbenchmark instances. The experimental results show that the approachis very competitive and it clearly outperforms previous ACO proposalsfor LOP.
A New Precedence-Based Ant Colony Optimization for Permutation Problems
Alfredo Milani;
2017-01-01
Abstract
In this paper we introduce ACOP, a novel ACO algorithmfor solving permutation based optimization problems. The main noveltyis in how ACOP ants construct a permutation by navigating the spaceof partial orders and considering precedence relations as solution components.Indeed, a permutation is built up by iteratively adding precedencerelations to a partial order of items until it becomes a total order, thus thecorresponding permutation is obtained. The pheromone model and theheuristic function assign desirability values to precedence relations. AnACOP implementation for the Linear Ordering Problem (LOP) is proposed.Experiments have been held on a large set of widely adopted LOPbenchmark instances. The experimental results show that the approachis very competitive and it clearly outperforms previous ACO proposalsfor LOP.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
