2014
DOI: 10.1016/j.ins.2014.05.039
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A new hybrid imperialist swarm-based optimization algorithm for university timetabling problems

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Cited by 35 publications
(32 citation statements)
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References 41 publications
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“…First, we compare the algorithms with an average number of evaluation functions callings. The results are as follows: FOA is better than the others for F1(2), F2(10), F3(5), F4(5), F5(5) and F7 (5); PSO is better than the other algorithms for F2 (5) and F7(10); and WCC is better than the others for F3(10), F4(10), F5(10), F6(5), F6(10), F8(5) and F8 (10).…”
Section: Table Average Values Shown Inmentioning
confidence: 95%
See 1 more Smart Citation
“…First, we compare the algorithms with an average number of evaluation functions callings. The results are as follows: FOA is better than the others for F1(2), F2(10), F3(5), F4(5), F5(5) and F7 (5); PSO is better than the other algorithms for F2 (5) and F7(10); and WCC is better than the others for F3(10), F4(10), F5(10), F6(5), F6(10), F8(5) and F8 (10).…”
Section: Table Average Values Shown Inmentioning
confidence: 95%
“…Improving a global exploration of a combination of floods of bee colony algorithm is mentioned as method's goals. Moreover, it was applied to two real datasets [5]. The heat transfer optimization algorithm was inspired by both the law of heat transfer and thermodynamics [6].…”
Section: Introductionmentioning
confidence: 99%
“…Optimasi himpunan dengan beberapa kriteria variabel sebagai input akan menghasilkan keputusan dengan memperhatikan batasan yang terkait untuk menghasilkan jadwal kuliha. Model dataset penjadwalan mata kuliah adalah sebagai berikut (Fong et al, 2014):…”
Section: Model Permasalahan Penjadwalan Mata Kuliahunclassified
“…Hybridization of meta-heuristic approaches has in recent years proven to be effective in solving scheduling and related resource allocation problems [9]. This is particularly the case where multiple objectives are present within the evaluation function.…”
Section: B Cactooptmentioning
confidence: 99%
“…The hybridization of these algorithms utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained [9].…”
Section: B Cactooptmentioning
confidence: 99%