Engineering and Technology Journal

Abstract

In this paper we introduce a modified ant system optimization algorithm,
we call it the multistage ant system optimization (MS-ASO). This modified algorithm
have many advantageous like releasing ants from local optima, enabling ants to accept
temporary bad solution in order to find better one later, improving the diversification
by forcing (not encouraging) ant to search new parts of the solution space, and also
pass information about the global best solution between the predetermined number of
iterations/stages. We test our modified algorithm on some benchmark problems of the
traveling sales man problem to see how good it is, the result we get was encouraging
that is we succeed in reducing the number of calculations (iterations) and we also find
new optimum solution (i.e. routes) for some benchmark problems which are better
(i.e. shortest) than published routes.