Search results for "Combinatorial Optimization"
showing 10 items of 59 documents
Intelligent Multi-Start Methods
2018
Heuristic search procedures aimed at finding globally optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored, which constitutes a multi-start procedure. In this chapter we describe the best known multi-start methods for solving optimization problems. We also describe their connections with other metaheuristic methodologies. We propose classifying these methods in terms of their use of randomization, memory and degree of rebuild. We also present a computational comparison of these methods on solvi…
Scatter Search and Path-Relinking: Fundamentals, Advances, and Applications
2010
Scatter search is an evolutionary metaheuristic that explores solution spaces by evolving a set of reference points, operating on a small set of solutions while making only limited use of randomization. We give a comprehensive description of the elements and methods that make up its template, including the most recent elements incorporated in successful applications in both global and combinatorial optimization. Path-relinking is an intensification strategy to explore trajectories connecting elite solutions obtained by heuristic methods such as scatter search, tabu search, and GRASP. We describe its mechanics, implementation issues, randomization, the use of pools of high-quality solutions …
New exact methods for the time-invariant berth allocation and quay crane assignment problem
2019
Abstract Efficient management of operations in seaport container terminals has become a critical issue, due to the increase in maritime traffic and the strong competition between ports. In this paper we focus on two seaside operational problems: the Berth Allocation Problem and the Quay Crane Assignment Problem, which are considered in an integrated way. For the continuous BACAP problem with time-invariant crane assignment we propose a new mixed integer linear model in which the vessels can be moored at any position on the quay, not requiring any quay discretization. The model is enhanced by adding several families of valid inequalities. The resulting model is able to solve instances with u…
Optimal selection of touristic packages based on user preferences during sports mega-events
2022
Sport mega-events, such as the Soccer World Cup or Olympic Games, attract many visitors from all over the world. Most of these visitors are also interested in, besides attending the sports events, visiting the host nation and the neighboring countries. In this paper, we focus on the upcoming FIFA World Cup Qatar 2022. As per the schedule of the tournament, a national team can play 7 matches at most. Therefore, a supporter will have six short breaks (of three to five days) between consecutive matches in addition to two longer ones, immediately before and after the tournament, during which they can plan some touris- tic trips. We study the problem faced by a touristic trip provider who wants …
Combinatorial Optimization for Artificial Intelligence Enabled Mobile Network Automation
2021
This chapter discusses combinatorial optimization techniques for enabling intelligent automation in mobile networks. A number of discrete optimization problems pertinent to mobile network automation can be solved effectively using artificial intelligence based combinatorial optimization approaches such as heuristics and metaheuristics. Relevant use-cases include both initial parameter assignment during network roll-out, and continuous optimization of configuration management parameters during network operation and maintenance. We discuss mobile network automation use-cases and motivation for using different heuristics and metaheuristics in designing network optimization algorithms. To this …
Variable Neighborhood Search for the Vertex Separation Problem
2012
The vertex separation problem belongs to a family of optimization problems in which the objective is to nd the best separator of vertices or edges in a generic graph. This optimization problem is strongly related to other well-known graph problems; such as the Path-Width, the Node Search Number or the Interval Thickness, among others. All of these optimization problems are NP-hard and have practical applications in VLSI, computer language compiler design or graph drawing. Up to know, they have been generally tackled with exact approaches, presenting polynomial-time algorithms to obtain the optimal solution for speci c types of graphs. However, in spite of their practical applications, these…
Scatter search for an uncapacitated p-hub median problem
2015
Scatter search is a population-based method that has been shown to yield high-quality outcomes for combinatorial optimization problems. It uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementation for an NP -hard variant of the classic p-hub median problem. Specifically, we tackle the uncapacitated r-allocation p-hub median problem, which consists of minimizing the cost of transporting the traffics between nodes of a network through special facilities that act as transshipment points. This problem has a significant number of applications in practice, such as the design of transportati…
Tabu search for min-max edge crossing in graphs
2020
Abstract Graph drawing is a key issue in the field of data analysis, given the ever-growing amount of information available today that require the use of automatic tools to represent it. Graph Drawing Problems (GDP) are hard combinatorial problems whose applications have been widely relevant in fields such as social network analysis and project management. While classically in GDPs the main aesthetic concern is related to the minimization of the total sum of crossing in the graph (min-sum), in this paper we focus on a particular variant of the problem, the Min-Max GDP, consisting in the minimization of the maximum crossing among all egdes. Recently proposed in scientific literature, the Min…
From First Principles to the Burrows and Wheeler Transform and Beyond, via Combinatorial Optimization
2007
AbstractWe introduce a combinatorial optimization framework that naturally induces a class of optimal word permutations with respect to a suitably defined cost function taking into account various measures of relatedness between words. The Burrows and Wheeler transform (bwt) (cf. [M. Burrows, D. Wheeler, A block sorting lossless data compression algorithm, Technical Report 124, Digital Equipment Corporation, 1994]), and its analog for labelled trees (cf. [P. Ferragina, F. Luccio, G. Manzini, S. Muthukrishnan, Structuring labeled trees for optimal succinctness, and beyond, in: Proc. of the 45th Annual IEEE Symposium on Foundations of Computer Science, 2005, pp. 198–207]), are special cases i…
Solving Graph Coloring Problems Using Learning Automata
2008
The graph coloring problem (GCP) is a widely studied combinatorial optimization problem with numerous applications, including time tabling, frequency assignment, and register allocation. The growing need for more efficient algorithms has led to the development of several GCP solvers. In this paper, we introduce the first GCP solver that is based on Learning Automata (LA). We enhance traditional Random Walk with LA-based learning capability, encoding the GCP as a Boolean satisfiability problem (SAT). Extensive experiments demonstrate that the LA significantly improve the performance of RW, thus laying the foundation for novel LA-based solutions to the GCP.