A Smell Agent Optimization Approach to Capacitated Vehicle Routing Problem for Solid Waste Collection

This paper proposes a new approach to solving a Capacitated Vehicle Routing Problem (CVRP) using a Smell Agent Optimization (SAO). A CVRP is modeled to fulfill the goal of determining the shortest total travel distance between node instances representing client locations. In recent times, various algorithms have been introduced to address a logistic problem with a more complex architecture. However, and most especially in practice, the CVRP becomes more complicated as the number of clients or pickup places expands. This makes it difficult to solve and consequently demands for more state-of-the-art algorithms. In this paper, the intelligence of smell detection of smell agent algorithm (SAO) is used to solve the CVRP model. Thirty-six instances of a waste management scenario were used to evaluate the performance of the SAO-CVRP against that of Firefly Algorithm (FA). Results showed the efficiency of SAO in solving the CVRP model which achieved 61% better result than FA.