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Metaheuristics in combinatorial optimization: overview and conceptual comparison (2003)

by C Blum, A Roli
Venue:ACM Comput. Surv
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Cuckoo search via Lévy flights

by Xin-she Yang, Suash Deb - Proceeings of World Congress on Nature & Biologically Inspired Computing (NaBIC 2009), IEEE Publications, USA , 2009
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Abstract - Cited by 106 (16 self) - Add to MetaCart
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...ingly popular. For example, particles swarm optimization (PSO) was inspired by fish and bird swarm intelligence, while the Firefly Algorithm was inspired by the flashing pattern of tropical fireflies =-=[2, 3, 6, 21, 22]-=-. These nature-inspired metaheuristic algorithms have been used in a wide range of optimization problems, including NP-hard problems such as the travelling salesman problem [2, 3, 6, 8, 10, 21]. The p...

Ant colony optimization: Introduction and recent trends

by Christian Blum , 2005
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Abstract - Cited by 70 (1 self) - Add to MetaCart
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Engineering optimisation by cuckoo search

by Xin-she Yang, Suash Deb - Int. J. Math. Modelling & Num. Optimisation , 2010
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Abstract - Cited by 52 (8 self) - Add to MetaCart
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Multi-path routing for multiple description video over wireless ad hoc networks

by Shiwen Mao, Y. Thomas Hou, Senior Member, Xiaolin Cheng, Student Member, Hanif D. Sherali, Scott F. Midkiff, Senior Member, Ya-qin Zhang - in Proc. IEEE INFOCOM 2005 , 2005
"... Abstract—We study the problem of multipath routing for double description (DD) video in wireless ad hoc networks. We follow an application-centric cross-layer approach and formulate an optimal routing problem that minimizes the application layer video distor-tion. We show that the optimization probl ..."
Abstract - Cited by 42 (13 self) - Add to MetaCart
Abstract—We study the problem of multipath routing for double description (DD) video in wireless ad hoc networks. We follow an application-centric cross-layer approach and formulate an optimal routing problem that minimizes the application layer video distor-tion. We show that the optimization problem has a highly complex objective function and an exact analytic solution is not obtainable. However, we find that a meta-heuristic approach such as genetic algorithms (GAs) is eminently effective in addressing this type of complex cross-layer optimization problems. We provide a detailed solution procedure for the GA-based approach. Simulation results demonstrate the superior performance of the GA-based approach versus several other approaches. Our efforts in this work provide an important methodology for addressing complex cross-layer op-timization problems, particularly those involved in the application and network layers. Index Terms—Ad hoc networks, cross-layer design, metaheuris-tics, multipath routing, multiple description video, optimization. I.
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...ce (not necessarily convex) and having less of a tendency to be trapped in a local optimum, as compared with other trajectory-based metaheuristics (e.g., simulated annealing (SA) and tabu search (TS) =-=[8]-=-). Using numerical results, we show that significant performance gains can be achieved by the GA-based approach over trajectory-based approaches. In order to examine the quality of GA solutions, as we...

Finding Safety Errors with ACO

by Enrique Alba , Francisco Chicano , 2007
"... Model Checking is a well-known and fully automatic technique for checking software properties, usually given as temporal logic formulae on the program variables. Most model checkers found in the literature use exact deterministic algorithms to check the properties. These algorithms usually require h ..."
Abstract - Cited by 23 (3 self) - Add to MetaCart
Model Checking is a well-known and fully automatic technique for checking software properties, usually given as temporal logic formulae on the program variables. Most model checkers found in the literature use exact deterministic algorithms to check the properties. These algorithms usually require huge amounts of computational resources if the checked model is large. We propose here the use of a new kind of Ant Colony Optimization (ACO) model, ACOhg, to refute safety properties in concurrent systems. ACO algorithms are stochastic techniques belonging to the class of metaheuristic algorithms and inspired by the foraging behaviour of real ants. The traditional ACO algorithms cannot deal with the model checking problem and thus we use ACOhg to tackle it. The results state that ACOhg algorithms find optimal or near optimal error trails in faulty concurrent systems with a reduced amount of resources, outperforming algorithms that are the state-of-the-art in model checking. This fact makes them suitable for checking safety properties in large concurrent systems, in which traditional techniques fail to find errors because of the model size.

Multiple description video multicast in wireless ad hoc networks,” ACM/Kluwer Mobile Netw

by Shiwen Mao, Xiaolin Cheng, Y. Thomas Hou - Appl. J , 2006
"... Abstract. Multiple description (MD) coding is a new video coding technique that is uniquely suitable for video transport over wireless ad hoc networks. In this paper, we consider the problem of how to support video multicast with MD video in ad hoc networks. We follow an application-centric, cross-l ..."
Abstract - Cited by 21 (9 self) - Add to MetaCart
Abstract. Multiple description (MD) coding is a new video coding technique that is uniquely suitable for video transport over wireless ad hoc networks. In this paper, we consider the problem of how to support video multicast with MD video in ad hoc networks. We follow an application-centric, cross-layer routing approach with the objective of minimizing the overall video distortion. We propose an MD video multicast scheme where multiple source trees are used. Furthermore, each video description is coded into multiple layers in order to cope with diversity in wireless link bandwidths. Based on this multicast model, we formulate the cross-layer multicast routing as a combinatorial optimization problem and propose an efficient Genetic Algorithm (GA)-based metaheuristic solution procedure. Performance comparison with existing approaches show significant gains for a wide range of network operating conditions.
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...edure in the sequel. 3. A metaheuristic solution An effective strategy to address Problem OPT-MM is to view it as a “black-box” optimization problem and to explore an effective metaheuristic approach =-=[7]-=-. In particular, we find that Genetic Algorithms (GA) [4] are eminently suitable for addressing this type of complex problems. The basic framework for our GA-based multicast routing solution procedure...

On the Estimation of the Expected Performance of a Metaheuristic on a Class of Instances -- How Many Instances, how many runs?

by Mauro Birattari , 2004
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Abstract - Cited by 21 (9 self) - Add to MetaCart
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Accelerated particle swarm optimization and support vector machine for business optimization and applications

by Xin-she Yang, Suash Deb, Simon Fong - in: NDT 2011, Communications in Computer and Information Science , 2011
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... techniques for regression, classification and data mining [5, 9, 16, 19, 20, 24]. 1 On the other hand, metaheuristic algorithms also become powerful for solving tough nonlinear optimization problems =-=[1, 7, 8, 27, 32]-=-. Modern metaheuristic algorithms have been developed with an aim to carry out global search, typical examples are genetic algorithms [6], particle swarm optimisation (PSO) [7], and Cuckoo Search [29,...

Ant systems for a dynamic tsp: Ants caught in a traffic jam

by Casper Joost Eyckelhof, Marko Snoek, Multigator Vof - Ant Algorithms : Third International Workshop, ANTS 2002, volume 2463 / 2002 of Lecture Notes in Computer Science , 2002
"... Abstract. In this paper we present a new Ants System approach to a dynamic Travelling Salesman Problem. Here the travel times between the cities are subject to change. To handle this dynamism several ways of adapting the pheromone matrix both locally and globally are considered. We show that the str ..."
Abstract - Cited by 18 (0 self) - Add to MetaCart
Abstract. In this paper we present a new Ants System approach to a dynamic Travelling Salesman Problem. Here the travel times between the cities are subject to change. To handle this dynamism several ways of adapting the pheromone matrix both locally and globally are considered. We show that the strategy of smoothing pheromone values only in the area containing a change leads to improved results. 1
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...rithms have been developed [SH97, BDT99, DC99], of which Ant System (AS) was the first [DMC96]. These ACO algorithms have been successfully applied to a variety of combinatorial optimisation problems =-=[BR01]-=-. Like other metaheuristics ACO algorithms have proven their use for static problems, but less is known about their behaviour on dynamic problems. In dynamic problems the goal is not to find desirable...

MAGMA: A Multiagent Architecture for Metaheuristics

by Andrea Roli, Michela Milano - IEEE TRANS. ON SYSTEMS, MAN AND CYBERNETICS - PART B , 2002
"... In this work we introduce a multiagent architecture conceived as a conceptual and practical framework for metaheuristic algorithms (MAGMA, MultiAGent Metaheuristics Architecture). Metaheuristics can be seen as the result of the interaction among di erent kinds of agents: level 0 agents constructing ..."
Abstract - Cited by 18 (1 self) - Add to MetaCart
In this work we introduce a multiagent architecture conceived as a conceptual and practical framework for metaheuristic algorithms (MAGMA, MultiAGent Metaheuristics Architecture). Metaheuristics can be seen as the result of the interaction among di erent kinds of agents: level 0 agents constructing initial solutions, level-1 agents improving solutions and level-2 agents providing the high level strategy. In this framework, classical metaheuristic algorithms can be smoothly accommodated and extended, and new algorithms can be easily designed by defining which agents are involved and their interactions. Furthermore, with the introduction of a fourth level of agents, coordinating lower level agents, MAGMA can also describe, in a uniform way, cooperative search and, in general, any combination of metaheuristics. We propose
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