A Two-Stage Multi-Objective Allocation Model for Students’ Admission into Academic Departments in A Malaysian Public University

We develop, formulate, verify and later validate a multiobjective model of student admission. Through a two-stage optimization procedure the model seeks to maximize student admission and student allocation into departments and academic programmes respectively. In the first stage, we seek to determine the optimal number of new student intake in all the departments of a given faculty by observing the departments’ capacity limitations in terms of lecture rooms/halls availability, budget constraints, number of faculty members and affirmative action quota. The second stage concerns the application of the same procedure with the objective of determining the optimal allocation of students obtained in the first stage into the respective academic programmes within the same department with constraints unique to each academic programme. Every constraint has its own weightage besides its level of priority. We then describe the application of the model to the Faculty of Science & Technology of the Universiti Kebangsaan Malaysia with its five academic centres/departments and then to the Centre for Mathematical Sciences with its three academic programmes. For both stages, we compare the results of the preemptive goal programming model with the non preemptive weighted goal programming model to analyse the adaptability of the models to real situations. Sensitivity analyses of the results are done to gauge the reliability of the model. We hope that the results of the application will demonstrate the model’s capability to provide an optimal apportionment of student admission policy with regard to the number of student intake and allocation into the departmental academic programmes of a faculty, as well as recognizing the capacity limitations of each academic programme

STUDENT ENROLLMENT ALLOCATION INTO ACADEMIC DEPARTMENTS USING WEIGHTED GOAL PROGRAMMING

A weighted non-preemptive multi-criteria model is built to optimize the distribution of students into academic departments of a faculty by taking into account the limits of space capacity, financial allocation, the number of instructors and affirmative action quotas. Each constraint has a weight attached. This model is applied to the Faculty of Science and Technology, Universiti Kebangsaan Malaysia. The successful application demonstrates the ability of the weighted non-preemptive model to comply with the student intake requirement and constraints of academic departments in the faculty

Pemodelan matematik dalam pengurusan Aktiviti Pelancongan Rekreasi di Wetland Putrajaya (Mathematical modelling approach to the management of recreational tourism activities at Wetland Putrajaya)

Satu model matematik dibina bagi menilai pengurusan aktiviti pelancongan rekreasi di Wetland Putrajaya. Kajian ini menggunakan kaedah pengaturcaraan gol (PaG) dan perisian LINDO 6.1.untuk menyelesaikan masalah pelbagai objektif bagi memaksimumkan anggaran keuntungan aktiviti dan bilangan peserta yang terlibat. Tujuh aktiviti di Wetland Putrajaya yang terletak di bawah pengurusan Perbadanan Putrajaya telah dipilih sebagai kes kajian. Data dan maklumat rekod tahun 2008 dijadikan sebagai anggaran untuk kos dan bilangan peserta. Hasil kajian mendapati pihak Wetland Putrajaya boleh mencapai keuntungan lebih 40% daripada jumlah kos dan matlamat untuk memaksimumkan bilangan peserta bagi aktiviti yang terlibat juga tercapai

Q-Neutrosophic Soft Relation and Its Application in Decision Making

Q-neutrosophic soft sets are essentially neutrosophic soft sets characterized by three independent two-dimensional membership functions which stand for uncertainty, indeterminacy and falsity. Thus, it can be applied to two-dimensional imprecise, indeterminate and inconsistent data which appear in most real life problems. Relations are a suitable tool for describing correspondences between objects

Neurogenetic Algorithm for Solving Combinatorial Engineering Problems

Diversity of the population in a genetic algorithm plays an important role in impeding premature convergence. This paper proposes an adaptive neurofuzzy inference system genetic algorithm based on sexual selection. In this technique, for choosing the female chromosome during sexual selection, a bilinear allocation lifetime approach is used to label the chromosomes based on their fitness value which will then be used to characterize the diversity of the population. The motivation of this algorithm is to maintain the population diversity throughout the search procedure. To promote diversity, the proposed algorithm combines the concept of gender and age of individuals and the fuzzy logic during the selection of parents. In order to appraise the performance of the techniques used in this study, one of the chemistry problems and some nonlinear functions available in literature is used

On the interval zoro symmetric single step procedure IZSS2-5D for simultaneous bounding of simple polynomial zeros

A new method called the interval zoro symmetric single-step procedure IZSS2-5D which is an extension of the previous procedure IZSS2 is described. The numerical results using five test polynomials contributed to shorter CPU times and reduced number of iterations

Interval symmetric single-step procedure ISS2-5D for polynomial zeros

We analyzed the rate of convergence of a new modified interval symmetric single-step procedure ISS2-5D which is an extension from the previous procedure ISS2. The algorithm of ISS2-5D includes the introduction of reusable correctors δi(k) (i = 1, …, n) for k ≥ 0. Furthermore, this procedure was tested on five test polynomials and the results were obtained using MATLAB 2007 software in association with IntLab V5.5 toolbox to record the CPU times and the number of iterations

Generalized Q-Neutrosophic Soft Expert Set for Decision under Uncertainty

Neutrosophic triplet structure yields a symmetric property of truth membership on the left, indeterminacy membership in the centre and false membership on the right, as do points of object, centre and image of reflection. As an extension of a neutrosophic set, the Q-neutrosophic set was introduced to handle two-dimensional uncertain and inconsistent situations

On the performances of IMZSS2 method for bounding polynomial zeros simultaneously

This paper describes the extension of the interval symmetric single-step method IZSS2, namely the interval midpoint symmetric single-step IMZSS2 method which performs a forward-backward-forward step. The algorithm IMZSS2 introduced new reusable correctors where we always update the midpoints of the intervals at every step of the method. We will display the numerical results comparing the CPU times and number of iterations of both methods. The results show that the IMZSS2 method performs better both in CPU times and number of iterations as can be seen in the accompanied figures