This paper describes an exact ε-constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objective are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently ge...

Cross docking is a logistics strategy that strives to reduce inventory holding costs, shipping costs, and delays in delivering the products. In this research, an optimization model is presented for split loading and unloading products by suppliers and customers, vehicle routing with fuzzy possibilistic time window constraints among them, assignment of vehicles to cross dock, consolidation and i...

The use of population-based techniques to solve optimization problems is continuously increasing, as these kind of problems appears in a number of situations in real life. Many of these problems are of a combinatorial nature, this means that we have to find the ideal permutation of the parameters involved to reach the optimal solution. As the number of parameters increases, the difficulty to fi...

This article addresses the problem of converting a single-objective combinatorial into multi-objective one using Pareto front approach. Although existing algorithms can identify optimal solution in space, they fail to satisfy constraints while achieving performance. To address this issue, we propose artificial bee colony optimization algorithm with classical theme called fitness sharing. approa...

in this paper, a novel multi-objective bus stop location model is proposed, which considers not only the coverage of demand and minimization of access time but also the necessities of suitable stops for transit network design phase. three objective functions are considered including minimizing (i) sum of the total access distance (time), (ii) the weighted combination of stops, and (iii) the num...