Evolutionary computation is inspired by nature in order to formulate metaheuristics capable to optimize several kinds of problems. A family of algorithms has emerged based on this idea; e.g. genetic algorithms, evolutionary strategies, particle swarm optimization (PSO), ant colony optimization (ACO), etc. In this paper we show a populationbased metaheuristic inspired on the gravitational forces...

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...

We consider the application of a new metaheuristic technique that we have proposed, known as PROBE (Population Reinforced Optimization Based Exploration), to the multiconstraint knapsack problem (MKP). In the current section, we begin by giving a brief introduction to PROBE; we then briefly review other metaheuristic approaches for the MKP. In Section 2, we describe our PROBE approach for the M...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

This paper is concerned with an aspect of the design of metaheuristic algorithms, such as evolutionary algorithms, tabu search and ant colony optimization. The topic that is considered is how problems can be represented when they are given to a metaheuristic algorithm. A particular difficulty is presented, viz. the “bottleneck”, where the problem is artificially converted into a new representat...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

Main methods, algorithms and applications of the Variable Neighborhood Search metaheuristic are surveyed, in view of a chapter of the Encyclopedia of Optimization.