Vehicle routing problem in a medical facility waste collection company: a comparative analysis of guided local search, simulated annealing and tabu search algorithm - Michael Anderson; Sumarsono Sudarto (International Journal of Technology)
Vehicle Routing Problem (VRP) is closely related to real-life situations, particularly in logistics. Therefore, this research aimed to 1) solve VRP problem faced by a waste management company by comparing three algorithms, namely guided local search, tabu search, and simulated annealing. 2) summarize the development of VRP by comparing several variants, and 3) assess the environmental impact through sensitivity analysis. The combined VRP variants are described as the Heterogeneous Fleet Distance Constrained Capacitated VRP with Time Windows because they reflect the current situation of the waste management company. In this context, a model was developed using Python programming language, specifically with a library called Ortools by Google, which is specialized for combinatorial optimization problem. The tests showed that the best algorithm for solving VRP was the path most constrained arc, used as the initial solution generator and guided local search as the optimization algorithm. This combination produced the best result for distance optimization, though it did not address workload balance and average working time. Another conclusion is that the total distance would increase by having more constraints and dimensions.