An Architecture for Solving Sequencing and Resource Allocation Problems Using Approximation Methods

In the search for better optimisation techniques, new methods that mix artificial intelligence and operations research have emerged. Search heuristics are integrated with optimisation algorithms. Approximation methods, like Hill Climbing, Simulated Annealing, and Tabu Search, that have been used wit...

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Veröffentlicht in:The Journal of the Operational Research Society Jg. 49; H. 1; S. 52 - 65
Hauptverfasser: Nussbaum, M., Sepúlveda, M., Singer, M., Laval, E.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basingstoke Macmillan Press 01.01.1998
Palgrave
Taylor & Francis Ltd
Schlagworte:
Applied sciences
Approximation
Artificial intelligence
Budget allocation
Exact sciences and technology
Expert systems
Flows in networks. Combinatorial problems
Heuristic
Heuristics
Neighborhoods
Operational research and scientific management
Operational research. Management science
Operations research
Optimization
Optimization techniques
Problem solving
Resource allocation
Scheduling
Sequencing
Sequential scheduling
Statistical analysis
Taboos
Theoretical Papers
Search strategy
Approximation
Architecture
User interface
Combinatorial problem
Resource allocation
Heuristic method
Knowledge base
Artificial intelligence
Sequencing
Optimization
ISSN:0160-5682, 1476-9360, 0160-5682
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Beschreibung
Zusammenfassung:In the search for better optimisation techniques, new methods that mix artificial intelligence and operations research have emerged. Search heuristics are integrated with optimisation algorithms. Approximation methods, like Hill Climbing, Simulated Annealing, and Tabu Search, that have been used with success in combinatorial optimisation problems, are one of such research lines. This paper presents the key elements of approximation methods and combines them in a tool appropriate for solving sequencing and resource allocation problems. The system permits a clear division between problem specification and problem solving, allowing a declarative representation and therefore minimising developing costs. The key issues discussed in this work are a model for representing this class of problems in a standard form, a set of strategies for applying the approximation methodology, and an expert system that dynamically manipulates the strategies' parameters.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0160-5682
1476-9360
0160-5682
DOI:10.1038/sj.jors.2600479