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Journal ArticleDOI

An immunity-based ant colony optimization algorithm for solving weapon–target assignment problem

TLDR
An immunity-based ant colony optimization (ACO) algorithm for solving weapon–target assignment (WTA) problems is proposed and from the simulation for those WTA problems, the proposed algorithm indeed is very efficient.
About
This article is published in Applied Soft Computing.The article was published on 2002-08-01. It has received 211 citations till now. The article focuses on the topics: Weapon target assignment problem & Generalized assignment problem.

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Citations
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Journal ArticleDOI

A comprehensive review on solar PV maximum power point tracking techniques

TL;DR: In this article, a state of the art review on various maximum power point techniques for solar PV systems covering timeworn conventional methods and latest soft computing algorithms is presented to date critical analysis on each of the method in terms of tracking speed, algorithm complexity, dynamic tracking under partial shading and hardware implementation is not been carried out.
Journal ArticleDOI

Application areas of AIS: The past, the present and the future

TL;DR: This paper attempts to suggest a set of problem features that it believes will allow the true potential of the immunological system to be exploited in computational systems, and define a unique niche for AIS.

Application areas of AIS: the past, present and future.

Emma Hart, +1 more
TL;DR: In this paper, the authors take a step back and reflect on the contributions that the Artificial Immune Systems (AIS) has brought to the application areas to which it has been applied, and suggest a set of problem features that they believe will allow the true potential of the immunological system to be exploited in computational systems.
Journal ArticleDOI

Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment

TL;DR: The proposed GA-ACO algorithm is to enhance the performance of genetic algorithm by incorporating local search, ant colony optimization (ACO), for multiple sequence alignment and has superior performance when compared to other existing algorithms.
Journal ArticleDOI

Applying hybrid meta-heuristics for capacitated vehicle routing problem

TL;DR: A hybrid algorithm of simulated annealing and tabu search is applied to solve capacitated vehicle routing problem and shows that the proposed algorithm is competitive with other existing algorithms for solving CVRP.
References
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Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI

Equation of state calculations by fast computing machines

TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Journal ArticleDOI

Ant system: optimization by a colony of cooperating agents

TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Journal ArticleDOI

Ant colony system: a cooperative learning approach to the traveling salesman problem

TL;DR: The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and it is concluded comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.
BookDOI

Swarm intelligence: from natural to artificial systems

TL;DR: This chapter discusses Ant Foraging Behavior, Combinatorial Optimization, and Routing in Communications Networks, and its application to Data Analysis and Graph Partitioning.
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