In the last few years a significant number of ant colony optimization (ACO) algorithms have been proposed for tackling multi-objective optimization problems. In this paper, we propose a software framework that allows to instantiate the most prominent multiobjective ACO (MOACO) algorithms. More importantly, the flexibility of this MOACO framework allows the application of automatic algorithm con...

This report is devoted to Multiobjective Combinatorial Optimization techniques. In particular, the Ant Colony Optimization metaheuristic and its possible multi-criteria extensions are analysed and impirically investigated on the wellknown Traveling Salesman Problem. The second part of this work presents a quite novel approach for doing Relational Multicriteria Clustering. Besides providing the ...

Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a job-sequence that minimizes the overall tardine...

Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimi...

Constraint Cellular ant algorithm is a new optimization method for solving real problems by using both constraints method, the evolutionary rule of cellular, graph theory and the characteristics of ant colony optimization. Multi-objective vehicle routing problem is very important and practical in logistic research fields, but it is difficult to model and solve because objectives have complicate...

Ant Colony Optimization is a relatively new meta-heuristic that has proven its quality and versatility on various combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The paper introduces an Ant Colony Optimization approach to solve the problem of determining a job-sequence that minimizes the overall tardine...

Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimizatio...

Research on a new metaheuristic for optimization is often initially focused on proof of concept applications. Time and cost are the most important factors to be considered in every construction project. Over the years, many research studies have been conducted to model the time-cost relationship. Construction planners often face the challenge of optimum resources utilization to compromise betwe...

A direct search approach to determine optimal reservoir operating is proposed with ant colony optimization for continuous domains (ACOR). The model is applied to a system of single reservoir to determine the optimum releases during 42 years of monthly steps. A disadvantage of ant colony based methods and the ACOR in particular, refers to great amount of computer run time consumption. In this st...

Traditional tour route planning mostly depends on the planner’s experience. However, whether tour route planning is appropriate or not has a considerable impact on the time and cost of the tour. Good planning can save unnecessary waiting time, avoid wasted operating costs, and contribute to the enhancement of the quality of tourism. Therefore, this study applied the ant colony optimization algo...