The Ant Colony Optimization algorithm was originally conceptualized as an algorithm for solving combinatorial optimization problems. In recent years, it has shown that the ACO metaheuristic can be extended such that it can handle both continuous and mixed variable optimization problems. In this paper we present an constraint-capable extension of Socha and Dorigo’s ACOR and ACOMV .

The Ant System is a distributed metaheuristic that combines an adaptive memory with a local heuristic function to repeatedly construct solutions of hard combina-torial optimization problems. We present in this paper an improved ant system algorithm for the Vehicle Routing Problem with one central depot and identical vehicles. Computational results on fourteen benchmark problems from the literat...

In this paper a metaheuristic algorithm composed of particle swarm, ray optimization, and harmony search (HRPSO) is presented for optimal design of truss structures. This algorithm is based on the particle swarm ray origin making is used to update the positions of the particles, and for enhancing the exploitation of the algorithm the harmony search is utilized. Numerical results demonstrate the...

Traditionally, project scheduling and material planning have been treated independently. In this research, a mixed integer programming model is presented to integrate project scheduling and materials ordering problems. The goal is to minimize the total material holding and ordering costs. In addition, an efficient metaheuristic algorithm is proposed to solve the model. The proposed algorithm is...

the urban waste collection is one of the major municipal activities that involves large expenditures and difficult operational problems. also, waste collection and disposal have high expenses such as investment cost (i.e. vehicles fleet) and high operational cost (i.e. fuel, maintenance). in fact, making slight improvements in this issue lead to a huge saving in municipal consumption. some inci...

Efficiency of reinforced concrete (RC) design can be measured by finding the design with minimum cost within all possible ones that satisfied security conditions. This task is difficult because RC members consisting of two materials; concrete and steel bars with different material properties i.e., compressive and tensile strength, elasticity modulus, and unit material costs. Thus, an additional...

Branch and Bound Algorithms based on Interval Arithmetic permit to solve exactly continuous (as well as mixed) non-linear and non-convex global optimization problems. However, their intrinsic exponential time-complexities do not make it possible to solve some quite large problems. The idea proposed in this paper is to limit the memory available during the computations of such a global optimizat...

The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Prob...

Mesh partitioning is an important problem that has extensive applications in many areas. Multilevel algorithms are a successful class of optimization techniques which addresses the mesh partitioning problem. In this paper we present an enhancement of the technique that uses nature inspired metaheuristic to achieve higher quality partitions. We apply and study a multilevel ant-colony (MACO) opti...

This paper demonstrates that metaheuristic algorithms can provide a useful general framework for estimating both linear and nonlinear econometric models. Two metaheuristic algorithms—firefly and accelerated particle swarm optimization—are employed in the context of several quantile regression models. The algorithms are stable and robust to the choice of starting values and the presence of vario...