Neighborhood based heuristics for a Two-level Hierarchical Location Problem with modular node capacities

In many telecommunication network architectures a given set of client nodes must be served by different kinds of facility, which provide di fferent services and have diff erent capabilities. Such facilities must be located and dimensioned in the design phase. We tackle a particular location problem in which two sets of facilities, mid level and high level, … Read more

Food Regulated Pareto Multi-Species: a new ACO Approach for the Multi-objective Shortest Path Problem

The use of metaheuristics in Multi-objective Combinatorial Optimization, particularly Ant Colony Optimization (ACO), has grown recently. This paper proposes an approach where multi-species ants compete for food resources. Each species has its own search strategy and do not access pheromone information of other species. As in nature, successful ant populations are allowed to grow, whereas … Read more

A biased random-key genetic algorithm for job-shop scheduling

This paper presents a local search, based on a new neighborhood for the job-shop scheduling problem, and its application within a biased random-key genetic algorithm. Schedules are constructed by decoding the chromosome supplied by the genetic algorithm with a procedure that generates active schedules. After an initial schedule is obtained, a local search heuristic, based … Read more

A biased random-key genetic algorithm for job-shop scheduling

This paper presents a local search, based on a new neighborhood for the job-shop scheduling problem, and its application within a biased random-key genetic algorithm. Schedules are constructed by decoding the chromosome supplied by the genetic algorithm with a procedure that generates active schedules. After an initial schedule is obtained, a local search heuristic, based … Read more

On implementation of local search and genetic algorithm techniques for some combinatorial optimization problems

In this paper we propose the approach to solving several combinatorial optimization problems using local search and genetic algorithm techniques. Initially this approach was developed in purpose to overcome some difficulties inhibiting the application of above-mentioned techniques to the problems of the Questionnaire Theory. But when the algorithms were developed it became clear that them … Read more

Efficient Solutions for the Far From Most String Problem

Computational molecular biology has emerged as one of the most exciting interdisciplinary fields. It has currently benefited from concepts and theoretical results obtained by different scientific research communities, including genetics, biochemistry, and computer science. In the past few years it has been shown that a large number of molecular biology problems can be formulated as … Read more

New VNS heuristic for Total Flowtime Flowshop Scheduling Problem

This paper develops a new VNS approach to Permutational Flow shop Scheduling Problem with Total Flow time criterion. There are many hybrid approaches inthe problem’s literature, that make use of VNS internally, usually applying job insert neighbourhood followed by job interchange neighbourhood. In this study different ways to combine both neighbourhoods were examined. All tests … Read more

Biased random-key genetic algorithms with applications in telecommunications

This paper surveys several applications of biased random-key genetic algorithms (BRKGA) in optimization problems that arise in telecommunications. We first review the basic concepts of BRKGA. This is followed by a description of BRKGA-based heuristics for routing in IP networks, design of survivable IP networks, redundant server location for content distribution, regenerator location in optical … Read more

A hybrid Lagrangean heuristic with GRASP and path-relinking for set K-covering

The set multicovering or set K-covering problem is an extension of the classical set covering problem, in which each object is required to be covered at least K times. The problem finds applications in the design of communication networks and in computational biology. We describe a GRASP with path-relinking heuristic for the set K-covering problem, … Read more

A biased random-key genetic algorithm for the Steiner triple covering problem

We present a biased random-key genetic algorithm (BRKGA) for finding small covers of computationally difficult set covering problems that arise in computing the 1-width of incidence matrices of Steiner triple systems. Using a parallel implementation of the BRKGA, we compute improved covers for the two largest instances in a standard set of test problems used … Read more