Tag: software

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MAOS-TSP: Project Portal

MAOS-TSP [1] is a multiagent optimization system (MAOS) for solving the Traveling Salesman Problem (TSP). The source code can be downloaded here. Related Information: Please find other related code and software in our Source Code Library. Basic Description What’s New Directories & Files Command Line & Parameters Output Information References Contact License Information: You can

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MAOS-GCP: Project Portal

MAOS-GCP [1] is a cooperative group optimization system (MAOS) for solving the Graph Coloring Problem (GCP). Related Information: MAOS-GCP shares the MAOS kernel with other MAOS applications (e.g. MAOS-TSP, MAOS-FSP, MAOS-QAP, MAOS-QKP), and contains some modules that are specifically for tacking GCP. Please find other related code and software in our Source Code Library. Basic Description

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MAOS-QKP: Project Portal

MAOS-QKP is a multiagent optimization system (MAOS) for solving the Quadratic Knapsack Problem (QKP). Related Information: MAOS-QKP shares the MAOS kernel with other MAOS applications (e.g. Graph Coloring Problem (GCP) and Traveling Salesman Problem (TSP)). Please find other related code and software in our Source Code Library. Basic Description What’s New Directories & Files Command Line

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MAOS-FSP: Project Portal

MAOS-FSP [1] is a cooperative group optimization system (MAOS) for solving the Flowshop Scheduling Problem (FSP). MAOS-FSP shares the MAOS kernel with other MAOS applications (e.g. MAOS-GCP and MAOS-TSP), and contains some modules that are specifically for tacking FSP. Related Information: Please find other related code and software in our Source Code Library. Basic Description

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MAOS-QAP: Project Portal

MAOS-QAP [1] is a cooperative group optimization system (MAOS) for solving the Quadratic Assignment Problem (QAP). Related Information: MAOS-QAP shares the MAOS kernel with other MAOS applications (e.g. MAOS-GCP and MAOS-TSP), and contains some modules that are specifically for tacking QAP. Please find other related code and software in our Source Code Library. Basic Description

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Cooperative Group Optimization System (CGO)

Category : Projects

The cooperative group optimization (CGO) system consists of a group of intelligent agents cooperating with their peers in a sharing environment for realizing a common intention of finding high-quality solution(s) based on the landscape representation of an optimization task. Numerical Optimization CGO has also been applied on numerical optimization problem (NOP) to find solutions in high-dimensional nonlinear continuous space.

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Artificial Intelligence (AI) application to utilize search cues in combinatorial optimization

This is a method using AI techniques to solve a case of pure mathematics applications for finding narrow admissible tuples. The original problem is formulated into a combinatorial optimization problem. In particular, we show how to exploit the local search structure to formulate the problem landscape for dramatic reductions in search space and for non-trivial

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Social Cognitive Optimization (SCO): Project Portal

Social Cognitive Optimization (SCO) [1, 2] is an optimization algorithm for solving the (constrained) numerical optimization problem. SCO is an agent-based model based on the observational learning mechanism in human social cognition. In CGOS [3], SCO was hybridized with differential evolution (DE) to obtain better results than individual algorithms on a common set of benchmark

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Dissipative Particle Swarm Optimization (DPSO)

The dissipative particle swarm optimization (DPSO) is developed according to the self-organization of dissipative structure. The negative entropy is introduced into the particle swarm to construct an opening dissipative system that is far-from-equilibrium so as to driving the evolutionary process towards better fitness. Xiao-Feng Xie, Wen-Jun Zhang, and Zhi-Lian Yang. A dissipative particle swarm optimization.

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DEPSO Algorithm: Project Portal

DEPSO [1], or called DEPS, is an algorithm for (constrained) numerical optimization problem (NOP). DEPSO combines the advantages of Particle Swarm Optimization (PSO) and Differential Evolution (DE). It is incorporated into cooperative group optimization (CGO) system [2]. The DEPSO paper has been cited over 400 times with various applications. DEPSO was also implemented (by Sun

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