Solving University Scheduling Problem with a Memetic Algorithm

Abbaszadeh, Mortaza; Saeedvand, Saeed; Mayani, Hamid Asbagi

doi:10.11591/ij-ai.v1i2.512

Cited by 2 publications

(3 citation statements)

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“…However, we attempt to use maximum Constraints in scheduling for receive the best response in this paper that we will discuss them later. In this paper we assume all of considered Constraints in [15], (our previous work) and we work and improve implementing our purposed algorithm on that constraints in this paper.…”

Section: Constraintsmentioning

confidence: 99%

“…Michael W. Carter divides problem into several sections in his proposed method and uses a greedy algorithm and an algorithm based on Lagrange function for allocating time intervals and allocating classrooms, respectively [3]. Considering computational complexity of Genetic Algorithms, actions have been taken to increase their speed, and in this direction, Abramson D. &Abela J have3 taken advantage of parallel Genetic Algorithms in their research to solve the problem of designing timetables for schools and they have reported relatively high time advantage compared with normal genetic algorithms [10], Varac J et al have presented complete review on application of genetic algorithms in their research for designing time tables [11] and in our previous work in [15] we purpose a memetic algorithm to solving University Scheduling Problem that we improve final results here.…”

Section: Introductionmentioning

confidence: 99%

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A Fast Genetic Algorithm for Solving University Scheduling Problem

Abbaszadeh

Saeedvand

2014

IJ-AI

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University course timetabling is a NP-hard problem which is very difficult to solve by conventional methods, we know scheduling problem is one of the Nondeterministic Polynomial (NP) problems. This means, solving NP problems through normal algorithm is a time-consuming process (it takes days or months with available equipment) which makes it impossible to be solved through a normal algorithm like this. In purposed algorithm the problem of university class scheduling is solved through a new chromosome structure and modifying the normal genetic methods which really improves the solution in this case. We include lecturer, class and course information in presented algorithm, with all their Constraints, and it creates optimized scheduling table for weekly program of university after creating primary population of chromosomes and running genetic operators. In the final part of this paper we conclude from the results of input data analysis that the results have high efficiency compared with other algorithms considering maximum Constraints.

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Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fast Genetic Algorithm for Solving University Scheduling Problem

Abbaszadeh

Saeedvand

2014

IJ-AI

Self Cite

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“…Scheduling is a classic problem which commonly occurs in many corporations, such as in university, Abbaszadeh et al have applied Memetic Algorithm to solve university courses scheduling problem [1]; in transportation, Xiaoni et al have solved the optimal headway and bus scheduling combination of a bus lane line [2]; and in hospital, Agyei et al have developed nurse scheduling problem using goal programming [3].…”

Section: Introductionmentioning

confidence: 99%