Abstract
Problem statement: Southern Waste Management environment (SWM environment) is a company responsible for the collection and disposal of solid waste for the city of Johor Bahru, a city with over one million populations. The company is implementing an integrated solid waste management system where it involved in the optimization of resources to ensure the effectiveness of its services. Formulating this real life problem into vehicle routing problem with stochastic demand model and using some designed algorithms to minimize operation cost of solid waste management. Approach: The implementation of Ant Colony Optimization (ACO) for solving solid waste collection problem as a VRPSD model was described. A set of data modified from the well known 50 customers problems were used to find the route such that the expected traveling cost was minimized. The total cost was minimized by adopting a preventive restocking policy which was trading off the extra cost of returning to depot after a stock-out with the cost of returning depot for restocking before a stock-out actually occurs. For comparison purposes, Simulated Annealing (SA) was used to generate the solution under the same condition. Results: For the problem size with 12 customers with vehicle capacity 10 units, both algorithms obtained the same best cost which is 69.4358 units. But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. Conclusion: SA was able to obtain good solutions for small ranges especially small size of problem. For ACS, it is always provide good results for all tested ranges and problems sizes of the tested problem.
Highlights
The results indicate that proposed Ant Colony System (ACS) with local search algorithm produces better solutions compared to Simulated Annealing (SA) algorithm
The percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. This indicates that ACS gives the results in a more consistent manner compared to SA
The deviation of best costs for SA algorithm from the best cost of ACS is increasing as the demand ranges increases
Summary
(SWM) was established in line with Malaysian Government's decision on the National Privatization of Solid Waste Management. It was subsequently awarded the task of managing the storage, collection, transfer, haul, intermediate processing and disposal of solid waste in the Southern Region of Peninsular Malaysia by Economic Planning Unit of the Prime Minister's Department on Dec 21st, 1995. Applying the most environmentally sound technology available, SWM will strive to enhance the quality of solid waste management and cleaning services in the country. In April 1996, SWM was directed by the Government of Malaysia to take over the solid waste Management and public cleaning services from all
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