About 3ieThe International Initiative for Impact Evaluation (3ie) promotes evidence-informed equitable, inclusive and sustainable development. We support the generation and effective use of high-quality evidence to inform decision-making and improve the lives of people living in poverty in low-and middle-income countries. We provide guidance and support to produce, synthesise and quality assure evidence of what works, for whom, how, why and at what cost. 3ie working papersThese papers cover a range of content. They may focus on current issues, debates and enduring challenges facing development policymakers, programme managers, practitioners and the impact evaluation and systematic review communities. Policyrelevant papers in this series synthesise or draw on relevant findings from mixed-method impact evaluations, systematic reviews funded by 3ie, as well as other rigorous evidence to offer new analyses, findings, insights and recommendations. Papers focusing on methods and technical guides also draw on similar sources to help advance understanding, design and use of rigorous and appropriate evaluations and reviews. We also use this series to publish lessons learned from 3ie grant-making and contributions from 3ie's senior research fellows. About this working paperThis paper, Understanding India's self-help groups: an organisational anatomy of functionality in a district in Madhya Pradesh, presents findings of a qualitative research study on the functioning of women's self-help groups in one district in Madhya Pradesh. This paper is being made available as submitted. It has not been copyedited but has been formatted for publication by 3ie.

Abstract-This paper gives a general model for the faculty course assignment problem that is a zero-one nonlinear multiobjective programming problem. Because of the nonconvexity of the problem, linear membership function and exponential membership function are used to find optimal solutions. The model with fuzzy methods provides a more satisfactory solution to a course assignment problem than assigning with arbitrary weights. Keywords-Preferences based decision makers, zero-one multiobjective programming, faculty course problem; scalarization. I. INTRODUCTIONThe employee assignment problem is becoming more intricate now a day. Specially schools, colleges, industries, organizations, etc are facing scheduling problem for assigning task. For example, scheduling or assigning work means matching people, places, time slots, and facilities. Further it is very difficult to solve problems having so many constraints. Generally, constraint is two types hard and soft. The problem of faculty course assignment means to satisfy all the constraints like one subject to one teacher only, teacher preference to teach course, not exceeding load, all course is distributed according to preferences of teachers as well as administrator. So many researchers have carried out research in the field of assigning courses to faculty. [3]. Two-stage optimization model to maximize faculty course preferences in assigning faculty members to courses (stage 1) and then maximize faculty time preferences by allocating courses to time blocks (stage 2). These constraints, which are computationally more complex than the others, are recovered during the second stage, and a number of sub-problems, one for each day of the week, are solved for local optima by Badri [7]. Bloomfield and McShary [1] also considered faculty preferences in their heuristic approach. Kara and Ozdemir [8] developed a minimax approach to the faculty course assignment problem by considering faculty preferences. Asratian and Werra [13] considered a theoretical model which extends the basic class teacher model of timetabling. This model corresponds to some situations which occur frequently in the basic training programs of universities and schools. It has been shown that this problem is NP complete when founded in some sufficient conditions for the existence of a timetable. Kara and Ozdemir presented a min-max approach to the faculty course assignment problem by considering faculty preferences. This study is a continuation and generalization of the faculty-course assignment problem considered earlier by Ozdemir and Gasimov [14]. They constructed a multi objective 0-1 nonlinear model for the problem, considering participants' average preferences and explained an effective way for its solution.To optimal fuzzy classification of students, Amintoosi & Haddadnia [18] has used a fuzzy function to solve university course timetable by genetic programming problem. A hybrid fuzzy evolutionary algorithm has been presented by Rachmawati & Srinivasan [20] to multi objective resource allocation pro...