Treffer: Monte Carlo method for Multiple Knapsack Problem
Title:
Monte Carlo method for Multiple Knapsack Problem
Authors:
Source:
LSSC 2003 : large-scale scientific computing (Sozopol, 4-8 June 2003, revised papers)Lecture notes in computer science. :136-143
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 10 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Programmation mathématique, Mathematical programming, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Généralités, General, Aculeata, Arthropoda, Hymenoptera, Insecta, Invertebrata, Allocation ressource, Resource allocation, Asignación recurso, Capital, Formicoidea, Insecte social, Social insect, Insecto social, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode optimisation, Optimization method, Método optimización, Optimisation combinatoire, Combinatorial optimization, Optimización combinatoria, Problème combinatoire, Combinatorial problem, Problema combinatorio, Problème sac à dos, Knapsack problem, Problema mochila, Solution optimale, Optimal solution, Solución óptima, Recherche locale, Local search
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
CLPP - BAS, Acad. G. Bonchev, bl.25A, 1113 Sofia, Bulgaria
ISSN:
0302-9743
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Operational research. Management
Operational research. Management
Accession Number:
edscal.15692340
Database:
PASCAL Archive
Weitere Informationen
This paper describes Monte Carlo (MC) method for Multiple Knapsack Problem (MKP). The MKP can be defined as economical problem like resource allocation and capital budgeting problems. The Ant Colony Optimization (ACO) is a MC method, created to solve Combinatorial Optimization Problems (COPs). The paper proposes a Local Search (LC) procedure which can be coupled with the ACO algorithm to improve the efficiency of the solving of the MKP. This will provide optimal or near optimal solutions for large problems with an acceptable amount of computational effort. Computational results have been presented to assess the performance of the proposed technique.