46 research outputs found
A learning-based path relinking algorithm for the bandwidth coloring problem
This paper proposes a learning-based path relinking algorithm (LPR) for solving the bandwidth coloring problem and the bandwidth multicoloring problem. Based on the population path-relinking framework, the proposed algorithm integrates a learning-driven tabu optimization procedure and a path-relinking operator. LPR is assessed on two sets of 66 common benchmark instances, and achieves highly competitive results in terms of both solution quality and computational efficiency compared to the state-of-the-art algorithms in the literature. Specifically, the algorithm establishes 7 new upper bounds while matching the best known results for 56 cases. The impacts of the learning mechanism and the path relinking operators are investigated, confirming their critical role to the success of the proposed algorithm
Sonet Network Design Problems
This paper presents a new method and a constraint-based objective function to
solve two problems related to the design of optical telecommunication networks,
namely the Synchronous Optical Network Ring Assignment Problem (SRAP) and the
Intra-ring Synchronous Optical Network Design Problem (IDP). These network
topology problems can be represented as a graph partitioning with capacity
constraints as shown in previous works. We present here a new objective
function and a new local search algorithm to solve these problems. Experiments
conducted in Comet allow us to compare our method to previous ones and show
that we obtain better results
Algorithms for the minimum sum coloring problem: a review
The Minimum Sum Coloring Problem (MSCP) is a variant of the well-known vertex
coloring problem which has a number of AI related applications. Due to its
theoretical and practical relevance, MSCP attracts increasing attention. The
only existing review on the problem dates back to 2004 and mainly covers the
history of MSCP and theoretical developments on specific graphs. In recent
years, the field has witnessed significant progresses on approximation
algorithms and practical solution algorithms. The purpose of this review is to
provide a comprehensive inspection of the most recent and representative MSCP
algorithms. To be informative, we identify the general framework followed by
practical solution algorithms and the key ingredients that make them
successful. By classifying the main search strategies and putting forward the
critical elements of the reviewed methods, we wish to encourage future
development of more powerful methods and motivate new applications