JOURNAL ARTICLE

Object-oriented constraint logic programming for timetable planning

Safaai DerisSigeru OmatuHiroshi OhtaPathiah Abd Samat

Year: 1997 Journal:   International Journal of Systems Science Vol: 28 (10)Pages: 987-999   Publisher: Taylor & Francis

Abstract

This paper deals with an object-oriented approach to analysis, design, and implementation of constraint logic programming (CLP) for a timetabling system (TTS). Currently, it is difficult to maintain and port such systems to different environments. This is because by nature, timetabling problems are combinatorial, dynamics, and optimization-based. Using a conventional approach, changes to organization's policies and activities require updating of the model. Subsequently, computer programs need to be updated accordingly. These tasks have to be performed by experts who are scarcely available. In this paper, we show that maintainability and extendibility of object-oriented technologies enhance model formulation and maintenance by inheritance and polymorphism properties of classes and objects. The object-oriented approach also enhances constraint propagation and search by object interactions and communications. These advantages can be applied to other similar optimization-based systems such as planning and scheduling.

Keywords:
Constraint programming Maintainability Computer science Object-oriented programming Constraint logic programming Scheduling (production processes) Constraint (computer-aided design) Object (grammar) Programming language Constraint satisfaction Distributed computing Mathematical optimization Software engineering Theoretical computer science Artificial intelligence Probabilistic logic Engineering Mathematics Stochastic programming

Metrics

3
Cited By
0.51
FWCI (Field Weighted Citation Impact)
16
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Constraint Satisfaction and Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Scheduling and Timetabling Solutions
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Model-Driven Software Engineering Techniques
Physical Sciences →  Computer Science →  Software

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