Simulation-based Optimization of a Real-world Travelling Salesman Problem Using an Evolutionary Algorithm with a Repair Function
2015 (English)In: International Journal of Artificial Intelligence and Expert Systems, ISSN 2180-124X, Vol. 6, no 3, 27-39 p.Article in journal (Refereed) Published
This paper presents a real-world case study of optimizing waste collection in Sweden. The problem, involving approximately 17,000 garbage bins served by three bin lorries, is approached as a travelling salesman problem and solved using simulation-based optimization and an evolutionary algorithm. To improve the performance of the evolutionary algorithm, it is enhanced with a repair function that adjusts its genome values so that shorter routes are found more quickly. The algorithm is tested using two crossover operators, i.e., the order crossover and heuristic crossover, combined with different mutation rates. The results indicate that the order crossover is superior to the heuristics crossover, but that the driving force of the search process is the mutation operator combined with the repair function.
Place, publisher, year, edition, pages
Computer Science Journals , 2015. Vol. 6, no 3, 27-39 p.
Evolutionary Algorithm, Simulation-based Optimization, Travelling Salesman Problem, Waste Collection, Real-world Case Study
Other Engineering and Technologies not elsewhere specified
Research subject Technology
IdentifiersURN: urn:nbn:se:his:diva-11668OAI: oai:DiVA.org:his-11668DiVA: diva2:868142