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

Randomized heuristics for the regenerator location problem

Telecommunication systems make use of optical signals to transmit information. The strength of a signal in an optical network deteriorates and loses power as it gets farther from the source, mainly due to attenuation. Therefore, to enable the signal to arrive at its intended destination with good quality, it is necessary to regenerate it periodically … Read more

A biased random-key genetic algorithm for road congestion minimization

One of the main goals in transportation planning is to achieve solutions for two classical problems, the traffic assignment and toll pricing problems. The traffic assignment problem aims to minimize total travel delay among all travelers. Based on data derived from the first problem, the toll pricing problem determines the set of tolls and corresponding … Read more

A parallel multi-population biased random-key genetic algorithm for a container loading problem

This paper presents a multi-population biased random-key genetic algorithm (BRKGA) for the Single Container Loading Problem (CLP) where several rectangular boxes of different sizes are loaded into a single rectangular container. The approach uses a maximal-space representation to manage the free spaces in the container. The proposed algorithm hybridizes a novel placement procedure with a … Read more

A biased random-key genetic algorithm for routing and wavelength assignment

The problem of routing and wavelength assignment (RWA) in wavelength division multiplexing (WDM) optical networks consists in routing a set of lightpaths and assigning a wavelength to each of them, such that lightpaths whose routes share a common fiber are assigned different wavelengths. This problem was shown to be NP-hard when the objective is to … Read more

Path-relinking intensification methods for stochastic local search algorithms

Path-relinking is major enhancement to heuristic search methods for solving combinatorial optimization problems, leading to significant improvements in both solution quality and running times. We review its fundamentals and implementation strategies, as well as advanced hybridizations with more elaborate metaheuristic schemes such as genetic algorithms and scatter search. Numerical examples are discussed and algorithms compared … Read more