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Timetabling by Coloring and Clustering by Neuronal Networks

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dc.contributor.advisor ASSISI, COLLINS en_US
dc.contributor.author NITURKAR, PRANAV en_US
dc.date.accessioned 2022-06-06T08:50:30Z
dc.date.available 2022-06-06T08:50:30Z
dc.date.issued 2022-05
dc.identifier.citation 53 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/7017
dc.description.abstract Designing a university course timetable requires assigning events(course lectures, tutorials, colloquia) to locations(on/off-line classrooms) and time slots, while avoiding clashes - for example, lectures of two courses that a particular student subscribes to cannot run concurrently. In designing the timetable, we can consider the events(or classes) as the vertices of a graph and the conflicts between them as edges between the corresponding vertices. This formulation allows us to state the university timetabling problem as a graph vertex coloring problem. Vertices with the same color, in any coloring of such a graph, can give us the set of events that can share the same time-slot, while different colors represent groups of events that must be assigned different time-slots.We propose using the dynamics of neuronal networks to solve the graph coloring problem. We will assign neurons to each vertex of the constraint graph and interactions between them will be inhibitory. Inhibitory neurons compete with each other, when one fires, it prevents those connected to it from firing. Therefore, vertices with the same color do not compete and can fire synchronously. In earlier work by Chowdhary S. and Assisi C., this idea was used to arrive at solutions of the Sudoku puzzle which can also be mapped to a vertex coloring problem. Here we propose using this approach to solve a particular instance of the university timetabling problem. en_US
dc.language.iso en en_US
dc.subject Clustering en_US
dc.subject IISER Timetabling en_US
dc.subject Neuronal Networks en_US
dc.subject Timetabling en_US
dc.subject Graph Coloring en_US
dc.title Timetabling by Coloring and Clustering by Neuronal Networks en_US
dc.title.alternative A heuristic algorithm for the University Course Timetabling Problem using competitive neuronal networks. en_US
dc.type Thesis en_US
dc.type Dissertation en_US
dc.description.embargo no embargo en_US
dc.type.degree MS-exit en_US
dc.contributor.department Interdisciplinary en_US
dc.contributor.registration 20192026 en_US


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  • MS THESES [1705]
    Thesis submitted to IISER Pune in partial fulfilment of the requirements for the BS-MS Dual Degree Programme/MSc. Programme/MS-Exit Programme

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