linear programming faculty assignment problem

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A linear programming solution to the faculty assignment problem

1976, Socio-Economic Planning Sciences

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Computers & Operations Research

Masood Badri

shahadat hossain

Tarek El-Sakka

Timetable problem is a well-known multidimensional, constraint assignment problem that focuses in the assignment of courses to faculty members in classrooms within limited time slots. Hence, it is a challenging time-consuming problem facing universities and it belongs to the NP-hard class of problems. In particular, universities regularly need an optimal solution for the course timetable problem. However, a manual solution to this problem by considering all constraints usually requires a long time and hard work to offer proper, optimized solution. Specifically, timetabling problem scan be modeled as Constraint satisfaction problems (CSPs), which are combinatorial in nature. Particularly, a variety of approaches are used to investigate CSPs, such as constraint logic programming (CLP) that combines the declaratively of logic programming with the efficiency of methods from operations research and artificial intelligence. This paper introduces a model that applies CLP to the timetabling as a CSP on the use of an Optimization Programming Language (OPL). The proposed model is tested against real data obtained from the Community College (CC), at University of Sharjah (UoS) that has a so sophisticated timetable with much interlaced, limited resources and limited time slots.

Badri Prakash Ojha

Raed Al-Husain , Mohamad Hasan

Journal of Computer Science IJCSIS

Resource planning in university is a very hard management science problem. Faculty members are expensive resource that a university needs to utilize them efficiently and deploy them effectively for courses that they can teach. In this paper, we focus on one of the most important problems in the universities – the academic calendar which comprised of faculty-course assignment, course scheduling and timetabling. We propose an innovative two-steps approach to solve the problem using mathematical models to optimize the resource allocation while satisfying the faculty preferences. We also showcase using a real-world example how this problem is solved easily and solution improves the productivity of the staff and enhances the satisfaction of faculty.

Raed Alhussain , Mohamad Hasan

Developing university schedules that could take into account factors such as faculties' preferences to courses, timeslots, and classrooms, in a timely fashion while being unbiased and meeting university requirements, is a hurdle in many universities around the world.This paper exploits the use of three-stage integer goal programming (IGP) technique to solve the university scheduling problem, as an expansion of an earlier two-stage model attempt conducted by the authors. Segmenting the problem into three stages enabled reaching a complete schedule in a timely manner and a high satisfactory level among faculties, while meeting all university requirements. The output of every stage is used as an input to the following stage, and goals are satisfied using the priority sequence approach according to their order of importance based on some college, department, and major regulations and requirements. Povzetek: Z novo metodo IGP naredijo univerzitetni urnik.

Ibrahim AlJarah

Abstract University Courses Timetabling problem hasbeen extensively researched in the last decade. Therefore,numerous approaches were proposed to solve UCT prob-lem. This paper proposes a new approach to process asequence of meetings between instructors, rooms, andstudents in predefined periods of time with satisfying a setof constraints divided in variety of types. In addition, thispaper proposes new representation for courses timetablingand conflict-free for each time slot by mining instructorpreferences from previous schedules to avoid undesirabletimes for instructors. Experiments on different real datashowed the approach achieved increased satisfaction degreefor each instructor and gives feasible schedule with satisfy-ing all hard constraints in construction operation. Thegenerated schedules have high satisfaction degrees compar-ing with schedules created manually. The research conductsexperiments on collected data gathered from the computerscience department and other related departments in Jor-dan University of Science and Technology- Jordan

Tauseeq Tufail

Expert Systems with Applications

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