The Capacitated Arc Routing Problem under Fuzzy Demands with a Case Study

Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems, plus it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel, maintenances) and making small improvements in this area can lead to huge savings in municipal expenditures. Among the issues raised in this context, changes in the pattern of waste collection in order to explore different, and consequently considering the uncertainty of the data. Study of urban waste collection problem in terms of uncertainty can help managers and decision-makers to make appropriate decisions.
In this paper, The Capacitated Arc Routing Problem under fuzzy demands is described. Due to uncertain nature of demands (waste amount) and the difficulty of determining the real amount, a fuzzy chance constrained programming is designed to model the problem, based on the fuzzy credibility theory. A hybrid genetic algorithm incorporated with a heuristic algorithm, a simulated annealing, a genetic algorithm and a stochastic simulation is developed and proposed to solve the model. The experimental results have shown that the proposed algorithm has appropriate performance in comparison with CPLEX. At the end of paper, a case study in urban waste collection of Isfahan is implemented to determine the optimal policy in uncertain circumstances.