Software engineering aspects of constraint-based timetabling—a case study

Abbas, Abdulwahed; Tsang, Edward

doi:10.1016/s0950-5849(03)00107-1

Cited by 7 publications

(5 citation statements)

References 30 publications

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“…This is a more elaborate example than the previous ones (details are in [22]). It addresses a general system that can generate school and university timetables.…”

Section: The Timetabling Problemmentioning

confidence: 93%

“…Comparing and contrasting DEPICT with other existing similar languages in this domain has already been done in [16,22]. We provide here a brief summary.…”

Section: Depict Versus Other Similar Languagesmentioning

confidence: 95%

“…CSPs are in nature NP-hard problems; that is, they have no known algorithmic solutions that admit a polynomial execution time. Some formulations may be easier to solve than others by certain heuristics [15,20,22] , but the complexity of the problem does not change. However, what is certain is that the expressiveness of DEPCIT does not hinder problem formulation.…”

Section: Extensibilitymentioning

confidence: 99%

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DEPICT: A high-level formal language for modeling constraint satisfaction problems

Abbas

Tsang

Nasri

2008

Int. J. Autom. Comput.

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The past decade witnessed rapid development of constraint satisfaction technologies, where algorithms are now able to cope with larger and harder problems. However, owing to the fact that constraints are inherently declarative, attention is quickly turning toward developing high-level programming languages within which such problems can be modeled and also solved. Along these lines, this paper presents DEPICT, the language. Its use is illustrated through modeling a number of benchmark examples. The paper continues with a description of a prototype system within which such models may be interpreted. The paper concludes with a description of a sample run of this interpreter showing how a problem modeled as such is typically solved.

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“…This is a more elaborate example than the previous ones (details are in [22]). It addresses a general system that can generate school and university timetables.…”

Section: The Timetabling Problemmentioning

confidence: 93%

“…Comparing and contrasting DEPICT with other existing similar languages in this domain has already been done in [16,22]. We provide here a brief summary.…”

Section: Depict Versus Other Similar Languagesmentioning

confidence: 95%

Section: Extensibilitymentioning

confidence: 99%

See 1 more Smart Citation

DEPICT: A high-level formal language for modeling constraint satisfaction problems

Abbas

Tsang

Nasri

2008

Int. J. Autom. Comput.

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“…Alternatively, one could add a logic-based interface to ZDC to provide logicians with a more familiar language for describing their problems (e.g. see [Abbas & Tsang 2004]). Some recent developments that one could consider adding to ZDC include newer genetic algorithms [Aickelin and Dowsland, 2003] Constraint solving researchers may not be interested in writing interfaces for their solvers.…”

Section: Limitations and Future Researchmentioning

confidence: 99%

Towards a practical engineering tool for rostering

et al. 2007

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The profitability and morale of many organizations (such as factories, hospitals and airlines) are affected by their ability to schedule their personnel properly. Sophisticated and powerful constraint solvers such as ILOG, CHIP, ECLiPSe, etc. have been demonstrated to be extremely effective on scheduling. Unfortunately, they require non-trivial expertise to use. This paper describes ZDC-Rostering, a constraintbased tool for personnel scheduling that addresses the software crisis and fills a void in the space of solvers. ZDC-Rostering is easier to use than the above constraint-based solvers and more effective than Microsoft's Excel Solver. ZDC-Rostering is based on an open-source computer-aided constraint programming package called ZDC, which decouples problem formulation (or modelling) from solution generation in constraint satisfaction. ZDC is equipped with a set of constraint algorithms, including Extended Guided Local Search, whose efficiency and effectiveness have been demonstrated in a wide range of applications. Our experiments show that ZDC-Rostering is capable of solving realistic-sized and very tightly-constrained problems efficiently. ZDC-Rostering demonstrates the feasibility of applying constraint satisfaction techniques to solving rostering problems, without having to acquire deep knowledge in constraint technology. ZDC-Rostering

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“…En el 2004, Abbas y Tsang (2004) consideraron algunas restricciones nuevas en la solución de este problema (Los estudiantes debían ser pre registrados).…”

Section: Introductionunclassified

Combinación entre Algoritmos Genéticos y Aleatorios para la Programación de Horarios de Clases basado en Ritmos Cognitivos

Castrillón

2014

Inf. tecnol.

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ResumenSe ha diseñado un método basado en algoritmos evolutivos (genéticos y aleatorios) para programar los horarios de clases en una universidad. Esta metodología considera los ritmos cognitivos de los estudiantes que indican que es mejor enseñar algunas asignaturas en intervalos específicos de tiempo. Primero se describen las diferentes técnicas empleadas para desarrollar este problema. Luego se propone una nueva metodología basada en ritmos cognitivos y algoritmos evolutivos, para resolver todas las restricciones duras y blandas del problema. Finalmente se comparan diferentes metodologías para establecer cuál es la más eficiente. Se concluye que los algoritmos evolutivos son más eficientes que otras técnicas empleadas (19.5%) en la programación de horarios universitarios. Palabras clave: programación, horarios universitarios, algoritmos genéticos, función objetivo, restricciones Combination Between Genetic and Random Algorithms for Programing Class Schedule based on Cognitive Rhythms AbstractA method based on evolutionary algorithms (genetics and random) to plan class schedules in a university has been developed. This methodology considers the students' cognitive rhythms, which indicate that it is better to teach some subjects in some specific time intervals. First, the different techniques to solve this problem are described. Then, a new methodology based on cognitive rhythms and evolutionary algorithms is proposed, to solve the hard and soft constraints. Finally, different methodologies are compared to determine the most efficient one. It is concluded that evolutionary algorithms are more efficient than others techniques (19.5%) for planning class schedules.

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Software engineering aspects of constraint-based timetabling—a case study

Cited by 7 publications

References 30 publications

DEPICT: A high-level formal language for modeling constraint satisfaction problems

DEPICT: A high-level formal language for modeling constraint satisfaction problems

Towards a practical engineering tool for rostering

Combinación entre Algoritmos Genéticos y Aleatorios para la Programación de Horarios de Clases basado en Ritmos Cognitivos

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