Simulated annealing (SA) to vehicle routing problems with soft time windows

Abstract

The researcher has applied and develops the meta-heuristics method to solve Vehicle Routing Problems with
Soft Time Windows (VRPSTW). For this case there was only one depot, multi customers which each generally
sparse either or demand was different though perceived number of demand and specific period of time to
receive them. The Operation Research was representative combinatorial optimization problems and is known
to be NP-hard. In this research algorithm, use Simulated Annealing (SA) to determine the optimum solutions
which rapidly time solving. After developed the algorithms, apply them to examine the factors and the optimum
extended time windows and test these factors with vehicle problem routing under specific time windows by
Solomon in OR-Library in case of maximum 25 customers. Meanwhile, 6 problems are including of
C101, C102, R101, R102, RC101 and RC102 respectively. The result shows the optimum extended time windows
at level of 50%. At last, after comparison these answers with the case of vehicle problem routing under specific
time windows and flexible time windows, found that percentage errors on number of vehicles approximately
by -28.57% and percentage errors on distances approximately by -28.57% which this algorithm spent
average processing time on 45.5 sec/problems.