We present an exact partial enumerative algorithm for the maximum clique problem. The pruning device used is derived from graph colorings. Pruning of the search tree is accomplished not only by the number of colors used to color a tree subproblem but also by using information gained in the process of coloring. This leads to increased pruning which translates into improved computational performance. Experimental results on test problems are presented.

An exact algorithm for the maximum clique problem with accelerated pruning

Wireless communication is used in many different situations such as mobile telephony, radio and TV broadcasting, satellite communication, wireless LANs, and military operations. In each of these situations a frequency assignment problem arises with application specific characteristics. Researchers have developed different modeling ideas for each of the features of the problem, such as the handling of interference among radio signals, the availability of frequencies, and the optimization criterion.

/pdf/models-and-solution-techniques-for-frequency-assignment-3405o60ech.pdf

Models and solution techniques for frequency assignment problems

This paper deals with the automatic selection and configuration of base station sites for mobile cellular networks. An optimization framework based on simulated annealing is used for site selection and for base-station configuration. Realistic path-loss estimates incorporating terrain data are used. The configuration of each base station involves selecting antenna type, power control, azimuth, and tilt. Results are presented for several design scenarios with between 250 and 750 candidate sites and show that the optimization framework can generate network designs with desired characteristics such as high area coverage and high traffic capacity. The work shows that cellular network design problems are tractable for realistic problem instances.

/pdf/planning-effective-cellular-mobile-radio-networks-1d1eynxq51.pdf

Planning effective cellular mobile radio networks

http://www.info.univ-angers.fr/pub/hao/papers/EJOR09.pdf

A Memetic Algorithm for Graph Coloring

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals. In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization. Ant colony optimization (ACO) takes inspiration from the foraging behavior of some ant species. These ants deposit pheromone on the ground in order to mark some favorable path that should be followed by other members of the colony. Ant colony optimization exploits a similar mechanism for solving optimization problems. From the early nineties, when the first ant colony optimization algorithm was proposed, ACO attracted the attention of increasing numbers of researchers and many successful applications are now available. Moreover, a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO. The goal of this article is to introduce ant colony optimization and to survey its most notable applications

Ant Colony Optimization.

This paper describes a system, FASoft, for discrete channel frequency assignment. In practice, the assignment of frequencies in a network of compatible equipment is often done manually or by the use of a single computational technique. FASoft incorporates state-of-the-art heuristics, sequential assignment algorithms, and a maximal clique algorithm to aid in the assignment process. Lower bounding procedures are included into the system to assess the performance of the assignment techniques and to provide an assessment of how close a particular assignment is to the optimal. The results show that FASoft produces optimal solutions to several practical examples.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/97RS01866

FASoft: A system for discrete channel frequency assignment

Improving heuristics for the frequency assignment problem

The frequency assignment problem, known to be NPcomplete, is to find an assignment of radio frequencies to a set of transmitters in a region. The interference level between the frequencies assigned to different communication links has to be acceptable, since otherwise communication will be distorted. Consequently, constraints are defined on pairs of links that limit the choice of frequencies for these pairs. Usually, a fixed number of frequency channels are available with which to make an assignment. The aim is to produce an assignment which minimizes the number of constraint violations. This paper compares the results obtained from using simulated annealing, genetic algorithms and tabu search for determining such an assignment. We report on our computational experiments in terms of the quality of the solutions obtained for realistic, computer-generated problem instances. 1 I N T R O D U C T I O N The radio spectrum is a vital but limited natural resource and the demand for frequencies is outpacing the increase in the usable spectrum. It is therefore vital "Permission to make digital/hard copy of all or part of this material without fee is grained provided that copies are not made or distributed for profit or commercial advantage, the ACM copyright/server notice, the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery, Inc.(ACM). To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee." © 1996 ACM0-89791-820-7 96 0002 3.50 that the spectrum be managed in the most effective way possible. The management of the spectrum would be eased if frequencies could always be assigned in an optimum or neax-optimum manner, so that some interference measure is at a minimum. However, the assignment of radio frequencies for problems of a practical size remains a considerable challenge. Computing methods based on exact algorithms and graph theory are successful for small problems but out of the question for large problems. Methods based on sequential heuristics [8], which mimic the way the problem might be solved manually, are fast enough for large problems but give results which are well short of the best possible. The main objective is to assign radio frequencies to a number of transmitters subject to a number of constraints, such that minimum interference is suffered. Ideally zero interference is desired, but given the limited region within which the transmitters operate, a more reasonable goal is to minimise the interference for a fixed set of frequencies i.e. a fixed spectrum. The problem is NP-complete [1]. Hence, no known algorithm can generate an optimal solution in a time that can be expressed as a polynomial function of the problem size. The aim of this paper is to implement several local searchalgorithms that have dominated the recent literature, namely, simulated annealing, genetic algorithms and tabu search and to compare the results. Data based on realistic sets of constraints axe used as test problems. 2 F R E Q U E N C Y A S S I G N M E N T We shall consider the problem where radio communi-

S. U. Thiel

Papers

FASoft: A system for discrete channel frequency assignment

Improving heuristics for the frequency assignment problem

A comparison of local search algorithms for radio link frequency assignment problems