Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation

The aquaculture farming industry is one of the most important industries in Malaysia since it generates income to economic growth and produces main source of food for the nation. One of the pillars in aquaculture farming industries is formulation of food for the animal, which is also known as feed mix or diet formulation. However, the feed component in the aquaculture industry incurs the most expensive operational cost, and has drawn many studies regarding diet formulation. The lack of studies involving modelling approaches had motivated to embark on diet formulation, which searches for the best combination of feed ingredients while satisfying nutritional requirements at a minimum cost. Hence, this thesis investigates a potential approach of Evolutionary Algorithm (EA) to propose a diet formulation solution for aquaculture farming, specifically the shrimp. In order to obtain a good combination of ingredients in the feed, a filtering heuristics known as Power Heuristics was introduced in the initialization stage of the EA methodology. This methodology was capableof filtering certain unwanted ingredients which could lead to potential poor solutions. The success of the proposed EA also relies on a new selection and crossover operators that have improved the overall performance of the solutions. Hence, three main EA model variants were constructed with new initialization mechanism, diverse selection and crossover operators, whereby the proposed EAPH-RWS-Avg Model emerged as the most effective in producing a good solution with the minimum penalty value. The newly proposed model is efficient and able to adapt to changes in the parameters, thus assists relevant users in managing the shrimp diet formulation issues, especially using local ingredients. Moreover, this diet formulation strategy provides user preference elements to choose from a range of preferred ingredients and the preferred total ingredient weights

Produktiviti di Bahagian Pengeluaran Sebuah Kilang : Satu Kajian Kes

Production is one of the issues that are continuously being monitored. Thus, a case study is being done on the productivity of the production end of a factory that produces sieved sugar as its final product. This research is mainly to study the level of productivity in the production end of Kilang Gula FELDA Perlis. Since there was no previous study done, partial and multifactor productivity are used in determining a suitable index for measuring productivity level on the production end of KGFP. Multifactor productivity has been determined as a suitable measuring index for productivity level at KGFP. Shift productivity and work group are also being analyzed using three-month worth of data that begins on January 2002 and ends on March 2002. This study has shown that workers on the afternoon shift from 3.00pm to 11.OOpm have the highest productivity yield. However, the difference in productivity value between the three shifts is very small. As for shift groups, group A has shown the highest productivity level followed by group C and B respectively. Next, regression analysis is done to determine the factor that relates to the productivity. Result from this analysis has shown that raw material and salary gives a significant value towards the output

THE ALLOCATION OF FIRE STATIONS USING SET COVER APPROACHES

Fireman is one of the most significant job in our country with multiple important task especially during fire and accident. Thus, the allocation of sufficient fire station is vital to cover the whole community within specific time. Consequently, this paper aims to build a framework to determine the specific number of fire station to be allocated in order to serve the whole community in Changlun Town, Kedah using set cover approaches. This approach is regularly employ in allocating the minimum number of fire station to cover the specific area with specific time limit. This study uses one of the core model in set cover problem which is known as Location Set Cover Problem. This model is designed for determining the specific number of fire station to ensure that all area in Changlun are covered within 15 minutes time. Greedy heuristic is used as a technique to accomplish the objective of this paper and gives out the best solution by proposing a specific location of these fire stations. This solution can be a guidance to government in designing and developing Changlun in the future.Keywords: Set Cover, Location Set Cover Problem, Greedy Heuristic

Roulette-tournament selection for shrimp diet formulation problem

This paper aims to propose a new selection procedure for real value encoding problem, specifically for shrimp diet problem.This new selection is a hybrid between two well-known selection procedure; roulette wheel selection and binary tournament selection.Shrimp diet problem is investigated to understand the hard constraints and the soft constraints involved.The comparison between other existing selections is also described for evaluation purposes.The result shows that roulette-tournament selection is better in terms of number of feasible solutions achieved and thus suitable for real value encoding problem.However, the combination with other crossover or mutation might be investigated to find the most suited combination that can obtain better best so far solution

Investigating feed mix problem approaches: An overview and potential solution

Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. It is always critical to produce the best aquaculture diet at a minimum cost in order to trim down the operational cost and gain more profit. However, the feed mix problem becomes increasingly difficult since many issues need to be considered simultaneously.Thus, the purpose of this paper is to review the current techniques used by nutritionist and researchers to tackle the issues. Additionally, this paper introduce an enhance algorithm which is deemed suitable to deal with all the issues arise. The proposed technique refers to Hybrid Genetic Algorithm which is expected to obtain the minimum cost diet for farmed animal, while satisfying nutritional requirements. Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem

Decision Tree and Ordinal Logistic Regression Methods for Maintaining University Sutainability

Recently, there are lots of cases regarding the use of fake account and cyberbullying. The irresponsible attitude is badly affecting the motivation of individual who being attacked and ruining the reputation of organization involved. This study is conducted among university students that aims to determine the factors of choosing fake account as a medium to raise an issue and to identify the impact of cyberbullying towards university’s reputation. About 380 samples were taken from undergraduate and postgraduate students. The data was analyzed using Decision Tree and Ordinal Logistic Regression (ORD) methods. The results show that there are students who have experienced cyberbullying or cyber victimization, which caused by the lack of parental support. The analysis from ORD method shows that fake account could affect university’s reputation. Hence, this research hopefully capable to create awareness among university students and help them to proudly present their university’s great name throughout the world. This is important to ensure the sustainability of community and university

An Assignment Problem and Its Application in Education Domain: A Review and Potential Path

This paper presents a review pertaining to assignment problem within the education domain, besides looking into the applications of the present research trend, developments, and publications. Assignment problem arises in diverse situations, where one needs to determine an optimal way to assign n subjects to m subjects in the best possible way.With that, this paper classified assignment problems into two, which are timetabling problem and allocation problem. The timetabling problem is further classified into examination, course, and school timetabling problems, while the allocation problem is divided into student-project allocation, new student allocation, and space allocation problems. Furthermore, the constraints, which are of hard and soft constraints, involved in the said problems are briefly elaborated.In addition, this paper presents various approaches to address various types of assignment problem. Moreover, direction and potential paths of problem solving based on the latest trend of approaches are also highlighted.As such, this review summarizes and records a comprehensive survey regarding assignment problem within education domain, which enhances one's understanding concerning the varied types of assignment problems, along with various approaches that serve as solution

A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem

Distribution of work shifts and off days to nurses in a duty roster is a crucial task. In hospital wards, much effort is spent trying to produce workable and quality rosters for their nurses. However, there are cases, such as mandatory working days per week and balanced distribution of shift types that could not be achieved in the manually generated rosters, which are still being practiced. Hence, this study focused on solving those issues arising in nurse rostering problems (NRPs) strategizing on a hybrid of Ant Colony Optimization (ACO) algorithm with a hill climbing technique. The hybridization with the hill climbing is aiming at fine-tuning the initial solution or roster generated by the ACO algorithm to achieve better rosters. The hybrid model is developed with the goal of satisfying the hard constraints, while minimizing the violation of soft constraints in such a way that fulfill hospital’s rules and nurses’ preferences. The real data used for this highly constrained NRPs was obtained from a large Malaysian hospital. Specifically, three main phases were involved in developing the hybrid model, which are generating an initial roster, updating the roster through the ACO algorithm, and implementing the hill climbing to further search for a refined solution. The results show that at a larger value of pheromone, the chance of obtaining a good solution was found with only small penalty values. This study has proven that the hybrid ACO is able to solve NRPs with good potential solutions that fulfilled all the four important criteria, which are coverage, quality, flexibility, and cost. Subsequently, the hybrid model is also beneficial to the hospital’s management whereby nurses can be scheduled with balanced distribution of shifts, which fulfill their preferences as well

Potential grouper feed formulation based on evolutionary algorithm concept with a unique selection operator

The problems of insufficient wild catch grouper fish and the high demand in the market have increased the need of farming the grouper fish.In order to farm the grouper fish, there is a need to have abundant of trash fish as their feeds since grouper fish is a carnivorous fish.But, trash fish is dramatically expensive and hard to store, hard to maintain the quality of nutrients as well as the quantity throughout the years.Therefore, turning to formulated feed mix is the alternative. However, the issue is on its cost while providing quality feed mix.That leads to the search for an approach which could provide the most suitable feed ingredients and nutrients.One potential approach is the Evolutionary Algorithm (EA) which has been used to solve the feed formulation problems in poultry, shrimp and cattle.Hence, in this study, an EA-based approach with a refinement on using the standard deviation in the strategy of tournament selection has been proposed to minimize the total cost in formulating the feed of grouper fish.Results show that the lowest cost can be accepted while satisfying the nutrient requirements of grouper fish

Evolutionary algorithm approach for solving animal diet formulation

One of the pillars in animal farming industries is formulation of food for the animal, which is also known as diet formulation.However, the feed component in the aquaculture industry incurs the most expensive operational cost, and has drawn many studies regarding diet formulation.Hence, this study aims to solve animal diet formulation problem with ratio constraint using evolutionary algorithm approach.Actual data with 14 ingredients and 18 nutrients were taken into consideration.The result shows that evolutionary algorithm provides feasible solution in all runs. Experimentation on what-if scenario has proven that this evolutionary model is robust as it can adopt to changes in the parameter