A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling

A university course timetabling problem is a combination of optimization problems. The problems are more challenging when a set of events need to be scheduled in the time slot, to be located to the suitable rooms, which is subjected to several sets of hard and soft constraints. All these constraints that exist as regulations within each resource for the event need to be fulfilled in order to achieve the optimum tasks. In addition, the design of course timetables for universities is a very difficult task because it is a non-deterministic polynomial, (NP) hard problem. This problem can be minimized by using a Micro Genetic Algorithm approach. This approach, encodes a chromosome representation as one of the key elements to ensure the infeasible individual chromosome produced is minimized. Thus, this study proposes an encoding chromosome representation using one-dimensional arrays to improve the Micro Genetic algorithm approach to soft constraint problems in the university course schedule. The research contribution of this study is in developing effective and feasible timetabling software using Micro Genetic Algorithm approach in order to minimize the production of an infeasible individual chromosome compared to the existing optimization algorithm for university course timetabling where UNITAR International University have been used as a data sample. The Micro Genetic Algorithm proposed has been tested in a test comparison with the Standard Genetic algorithm and the Guided Search Genetic algorithm as a benchmark. The results showed that the proposed algorithm is able to generate a minimum number of an infeasible individual chromosome. The result from the experiment also demonstrated that the Micro Genetic Algorithm is capable to produce the best course schedule to the UNITAR International University

Design of an Information System for optimizing the Programming of nursing work shifts

Health institutions operate twenty-four hours a day, seven days a week. They face a demand that fluctuates daily. Unlike jobs with fixed hours and obligatory days off, in health, operational continuity is required. The allocation for nursing shifts generates a rotation of people for health services according to legal and casuistic guidelines. Assigning and planning shifts results in a workload that takes an average of five to six extra hours. Existing applications offer a partial solution because they do not consider the news and contingencies of a health service. A web application is presented that, given a list of nurses, historical shifts and restrictions, a work shift planning is generated. This application comes to support the current shift allocation method based on electronic spreadsheets. The development consists of two modules. The first module has a shift allocation algorithm developed in C ++ and the second module has a graphical interface. As a case study, a set of health services from Chile and Colombia was used. The services have a defined number of nurses, who work different shifts according to the role and need of the institution. The results obtained are similar to a historical one. The proposed system takes less time and delivers various files and parameters that can be useful for nurses, the service and the health institutio

Nurse Rostering: A Tabu Search Technique With Embedded Nurse Preferences

The decision making in assigning all nursing staffs to shift duties in a hospital unit must be done appropriately because it is a crucial task due to various requirements and constraints that need to be fulfilled. The shift assignment or also known as roster has a great impact on the nurses’ operational circumstances which are strongly related to the intensity of quality of health care. The head nurse usually spends a substantial amount of time developing manual rosters, especially when there are many staff requests. Yet, sometimes she could not ensure that all constraints are met. Therefore, this research identified the relevant constraints being imposed in solving the nurse rostering problem (NRP) and examined the efficient method to generate the nurse roster based on constraints involved. Subsequently, as part of this research, we develop a Tabu Search (TS) model to solve a particular NRP. There are two aspects of enhancement in the proposed TS model. The first aspect is in the initialization phase of the TS model, where we introduced a semi-random initialization method to produce an initial solution. The advantage of using this initialization method is that it avoids the violation of hard constraints at any time in the TS process. The second aspect is in the neighbourhood generation phase, where several neighbours need to be generated as part of the TS approach. In this phase, we introduced two different neighbourhood generation methods, which are specific to the NRP. The proposed TS model is evaluated for its efficiency, where 30 samples of rosters generated were taken for analysis. The feasible solutions (i.e. the roster) were evaluated based on their minimum penalty values. The penalty values were given based on different violations of hard and soft constraints. The TS model is able to produce efficient rosters which do not violate any hard constraints and at the same time, fulfill the soft constraints as much as possible. The performance of the model is certainly better than the manually generated model and also comparable to the existing similar nurse rostering model

MODEL GOAL PROGRAMMING DAN PENGOPTIMUMAN TAKLINEAR PADA PENJADWALAN PERAWAT

Penjadwalan perawat merupakan pekerjaan penting dalam operasional sebuah rumah sakit. Jika manajemen rumah sakit melakukan penjadwalan dengan baik maka akan berdampak pada kinerja perawat yang semakin baik. Salah satu indikator penjadwalan yang baik adalah tercapainya distribusi beban kerja yang merata bagi seluruh perawat. Namun demikian, adanya keterbatasan sumber daya untuk memenuhi kebutuhan rumah sakit menjadi kendala tersendiri dalam upaya mencapai keadilan. Dalam hal ini, goal programming dapat menjadi salah satu solusi untuk mengatasi kendala tersebut. Dalam penelitian ini, nonpreemptive goal programming digunakan untuk memecahkan masalah penjadwalan perawat. Tujuan model ini adalah untuk meminimumkan beberapa simpangan preferensi perawat terhadap banyaknya shift kerja dan libur. Kami juga memberikan alternatif penyelesaian penjadwalan perawat menggunakan model optimasi taklinear dengan meminimumkan ragam beban kerja pada setiap shift kerja dan libur. Model ini diaplikasikan pada penjadwalan perawat ruang rawat inap Rumah Sakit Umum Daerah Kota Bogor

Hybrid artificial intelligence technique for solving large, highly constrained timetabling problems

Timetabling problems are often hard and time-consuming to solve. Profits from full automatization of this process can be invaluable. Although over the years many solutions have been proposed, most of the methods concern only one problem instance or class. This paper describes a possibly universal method for solving large, highly constrained timetabling problems from different areas. The solution is based on evolutionary algorithm's framework, with specialized genetic operators and penalty-based evaluation function, and uses hyper-heuristics to establish its operating parameters. The method has been used to solve three different timetabling problems, which are described in detail, along with some results of preliminary experiments

Human Resource Management Practices and Organisational Performance : A Study on Administrators in Universiti Teknologi MARA

This quantitative research aims to determine the relationship between human resource management practices and performance management in Universiti Teknologi MARA. The study is conducted to the administrators who involve in the human resource matters and administration in all faculty, branch campus and department. Instrument of assessment questionnaire by Chand and Katou (2007) and Brewster and Hegewisch (1994) used to measure human resource management practices and instrument questionnaire by de Waal and Frijns (2011) to measure organisational performance. All variables in HRM practices have relationship with the organisational performance, where manpower planning and quality circle have the strongest relationship. Of the six hypotheses tested, five were substantiated and one was not. It is also indicated that quality circle has the most correlation effect on organisational performance

A time predefined variable depth search for nurse rostering

This paper presents a variable depth search for the nurse rostering problem. The algorithm works by chaining together single neighbourhood swaps into more effective compound moves. It achieves this by using heuristics to decide whether to continue extending a chain and which candidates to examine as the next potential link in the chain. Because end users vary in how long they are willing to wait for solutions, a particular goal of this research was to create an algorithm that accepts a user specified computational time limit and uses it effectively. When compared against previously published approaches the results show that the algorithm is very competitive

Nurse Rostering Problems: A Bibliographic Survey

10.1016/S0377-2217(03)00021-3European Journal of Operational Research1513447-460EJOR