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

Convective boundary layer flow in generalized Newtonian nanofluid under various boundary conditions

The four mathematical models of boundary layer flow solved under different boundary conditions. The first problem considered the unsteady squeezing flow of the Carreau nanofluid over the sensor surface, where three different nanoparticles were suspended in the base fluid. A comparison of the results of suspended materials in liquids proved that increased surface permeability leads to increased heat transfer. The second problem described the magnetohydrodynamics (MHD) Darcy-Forchheimer model, which considers Maxwell nanofluids' flow. It was observed that an increase in the Biot number coefficient increased heat transfer. The third problem evaluated activation energy and binary reaction effect on the MHD Carreau nanofluid model. Buongiorno nanofluid model was applied to shear-thinning or pseudoplastic fluid over the pereamble surface. The relationship between the activation energy and chemical reaction is influential and controls heat transfer processes. The fourth problem analyzed the radiative Sutterby model over a stretching/shrinking sheet towards stagnation point flow. Dual solutions were found using the scaling group transformation, which was examined by a stability approach. Such a problem found an increment in the suction parameter, the Deborah number, and the nanoparticle volume fraction delayed the flow separation. The influence of various pertinent parameters on the velocity and temperature distributions has been presented. The most relevant results by the forceful impacts of thermo-physical properties on fluids were analyzed through this work. Modeled equations are based on the conservation laws under the boundary layer approximation. The similarity transformation method is used to convert the governing partial differential equations into ordinary differential equations. They are then solved using a numerical technique, known as the Runge�Kutta-Fehlberg method with shooting technique in the MAPLE 17 or bvp4c method in the MATLAB 2019a

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

Menu Planning Model for Malaysian Boarding School Using Self-Adaptive Hybrid Genetic Algorithms

Malnutrition problem is the gravest single threat to the world's public health today. Statistics have showed that the number of under-nourished and over-nourished children and adolescents is increasing day by day. Thus, proper menu planning process among menu planners or caterers is important to avoid some diet-related diseases in the hture. Manual calculation of menu planning is unable to consider macronutrients and micronutrients simultaneously due to complexities of data and length of time. In this study, self-adaptive hybrid genetic algorithm (SHGA) approach has been proposed to solve the menu planning problem for Malaysian boarding school students aged 13 to 18 years old. The objectives of our menu planning model are to optimize the budget allocation for each student, to take into consideration the caterer's ability, to llfill the standard recommended nutrient intake (RNI) and maximize the variety of daily meals. New local search was adopted in this study, the insertion search with delete-and-create (ISDC) method, which combined the insertion search (IS) and delete-and-create (DC) local search method. The implementation of IS itself could not guarantee the production of feasible solutions as it only explores a small neighborhood area. Thus, the ISDC was utilized to enhance the search towards a large neighborhood area and the results indicated that the proposed algorithm is able to produce 100% feasible solutions with the best fitness value. Besides that, implementation of self-adaptive probability for mutation has significantly minimized computational time taken to generate the good solutions in just few minutes. Hybridization technique of local search method and self-adaptive strategy have improved the performance of traditional genetic algorithm through balanced exploitation and exploration scheme. Finally, the present study has developed a menu planning prototype for caterers to provide healthy and nutritious daily meals using simple and fhendly user interface

Planificación de la nutrición para lotes de gallinas ponedoras, usando técnicas de optimización lineal difusa

In this work the fuzzy formulation of the diet problem in the planning of the nutrition of the farms of laying hens is done, and then it is solved applying the methods proposed by Lai and Hwang and by Zimmermann.Finally, we solve a nutritional planning problem with twelve products of which 4 are diffuse and with 10 nutritional substances.En éste trabajo se hace la formulación difusa del problema de la dieta en la planificación de la nutrición de las granjas de gallinas ponedoras, luego se resuelve aplicando los métodos propuesto por Lai y Hwang y por Zimmermann. Finalmente, resolvemos un problema de planificación nutricional con doce productos de los cuales 4 son difusos y con 10 sustancias nutricionales

PARADIGMA EVOLUTIVO EN LA FORMULACIÓN DE RACIONES PARA GANADO BOVINO (EVOLUTIONARY PARADIGM IN THE FORMULATION OF RATIONS FOR BOVINE CATTLE)

ResumenEl interés de la industria ganadera por la salud del animal ha impulsado el estudio de la preparación de raciones con los nutrientes necesarios para un mayor rendimiento en la producción de leche. El cuidado de una buena alimentación está directamente relacionado con la calidad y cantidad de leche producida por una vaca. Este trabajo propone una técnica evolutiva para la formulación de raciones con el objetivo de maximizar la producción de leche en el ganado bovino. El problema de la formulación de raciones es complejo debido a que no sólo se considera su peso, edad, especie y estado físico del animal, sino también, factores como la proteína cruda digerible, los nutrientes totales digeribles y la materia seca digerible son importantes en este proceso. En este trabajo, un Algoritmo Genético con representación binaria es propuesto para resolver el problema en la formulación de raciones. Los resultados obtenidos muestran que la aplicación del Algoritmo Genético en la preparación de raciones es una alternativa muy competitiva y eficiente, que alcanza un mayor rendimiento que los métodos tradicionales en la producción de leche para ganado bovino.Palabra(s) Clave: Algoritmo genético, Nutrición animal, Nutrientes, Rendimiento. AbstractThis work proposes an evolutionary technique for the formulation of food rations with the objective to maximize milk production in cattle. The interest of the livestock industry by the animal's health has promoted the study of the preparation of rations with the necessary nutrients for increased performance in the production of milk. The care of a good power supply guarantees the quality and quantity of milk produced by a cow. The problem of ration formulation is complex due to the fact that not only is considered your weight, age and physical condition of the animal, but in addition, factors such as the digestible crude protein, total digestible nutrients and the digestible dry matter are important in this process. A Genetic Algorithm with binary representation is proposed in the formulation of rations. The results are interesting and competitive reaching greater performance in the production of milk.Keywords: Animal nutrition, Genetic algorithm, Nutrients, Performance

Book of abstract RUC-APS international conference 2021

This book includes the abstracts of accepted submissions to the 2nd International RUC-APS conference, held online from November 29th to December 2nd 2021

Route optimization in agricultural land treatment

Predmet istraţivanja doktorske disertacije je tretiranje poljoprivrednog zemljišta, odnosno kreiranje i izbor efikasnih ruta. Pregledom literature uoĉeno je da su u oblasti poljoprivrede rešavani razliĉiti lokacijski problemi, problemi alokacije i rutiranja. Znaĉajnu ulogu u odgovornom planiranju korišćenja poljoprivrednih resursa ima i prepoznavanje i rešavanje raznih optimizacionih problema koji se javljaju u procesu eksploatacije, o ĉemu svedoĉi i veliki broj istraţivanja koja se bave primenom metoda operacionih istraţivanja u ovoj oblasti. Problem koji se rešava se sastoji od izvršenja jedne vrste operacije na isparcelisanom poljoprivrednom zemljištu koje je potrebno tretirati korišćenjem avijacije. Karakteristike problema su: zemljište je isparcelisano i takve je površine da ga je nemoguće obraditi jednim preletom aviona; postoji nehomogena flota aviona i više potencijalnih letelišta koja se mogu koristiti za uzletanje i sletanje aviona; jednim preletom je moguće obraditi više parcela u zavisnosti od kapaciteta aviona. Prouĉavani problem se sastoji u odreĊivanju optimalnih ruta za dati broj aviona koji se koriste za tretiranje isparcelisanog poljoprivrednog zemljišta hemikalijama. Ovaj NP (Nondeterministic Polynomial) teţak problem je prikazan na grafu i predstavlja specijalnu varijantu roblema rutiranja vozila (The Vehicle Routing Problem - VRP) sa više depoa gde se generiše transportni plan za homogeni proizvod (hemikalije korišćene za tretiranje zemljišta) sa razliĉitih lokacija ponude (letelišta) do razliĉitih lokacija potraţnje (parcele) uz minimalne troškove. Da bi se jedno zemljište, podeljeno na parcele, efikasno tretiralo uz pomoć avijacije, potrebno je: izabrati letelišta koja će se koristiti za uzletanje i sletanje i odrediti alokaciju parcela letelištima, odrediti naĉin preleta svake parcele (obrada parcele, tj. izvršenje operacije nad parcelom) i redosled tretiranja parcela. Deo rešenja problema je i odreĊivanje broja potrebnih aviona, kao i struktura same flote. Kompleksnost problema i primeri većih dimenzija uslovili su formulisanje specijalne heuristike za rešavanje opisanog problema. Heuristikom su rešeni primeri većih dimenzija. Primenom razvijene specijalne heuristike dobijaju se planovi obrade - odnosno skup ruta kojima će poljoprivredni avion obraditi sve parcele na jednom poljoprivrednom zemljištu. Metoda obavijanja podataka (Data Envelopment Analysis – DEA) primenjena je za poreĊenje više planova obrade istog problema (dobijenih primenom heuristike) i odreĊivanje relativno efikasnih planova, a u okviru jednog efikasnog plana obrade primenom DEA metode su odreĊene relativno efikasne rute. U oba sluĉaja primenjen je CCR DEA izlazno orijentisani model. Predloţeni pristupi su testirani na primerima razliĉitih dimenzija i pokazalo se da se primenom DEA metode moţe oceniti efikasnost i izabrati planovi obrade i rute koje će se koristiti za tretiranje poljoprivrednog zemljišta.The subject of this research is the agricultural land treatment, i.e. determination and selection of efficient routes in the treatment of agricultural land. The review of available literature proved that in the field of agriculture, different location problems, problems of allocation and routing are being solved. Identification and solving various optimization problems that arise in the treatment of the agricultural land have an important role in responsible planning of agricultural resources and its usage, which is confirmed in large number of studies that deal with the application of operational research methods in this field. The problem that is solved consists of performing one type of operation on a parceled agricultural land using agricultural aviation. The characteristics of the problem are: the land is divided into parcels; the surface of the whole land can not be processed by a single plane overflight; a non-homogeneous fleet of aircraft is used; there exists several potential airfields that can be used as landing sites; processing of several parcels can be done with one overflight (depending on the capacity of the aircraft). The studied problem consists of determining the optimal routes for a given set of aircraft used for chemical treatment of arable agricultural land divided into parcels. This NP (Nondeterministic Polynomial) problem is represented on a graph and represents a specific variant of the multidepot vehicle routing problem (VRP) where a min-cost plan for the transportation of a homogeneous product (chemicals used for land treatment) from different supply locations (airfields) to different demand locations (agricultural parcels) should be generated. In order to effectively treat an agricultural land divided into parcels using agricultural aviation, it is necessary to: choose the airfields for take-offs and to determine the parcel allocation to the airfields, determine the treatment way for each parcel and sequence of parcel treatment. Part of the solution of the problem is to determine the number of required aircrafts, as well as the structure of the fleet itself. The complexity of the problem and large dimensions of the problem examples have led to the formulation of a special heuristics. These examples of larger dimensions are solved using formulated heuristics. The application of the special heuristics results in processing plans - that is, a set of routes the agricultural aircraft will take and process all the parcels on one agricultural land. DEA (Data Envelopment Analysis) method is applied to compare multiple processing plans (obtained using heuristics) and to determine relatively efficient plans. Relatively efficient routes are determined within one efficient processing plan, also by using DEA method. In both cases, an output-oriented DEA model is applied. The proposed approaches are tested on examples of different dimensions and it is shown that, by applying the DEA method, the efficiency and selection of cultivation plans and routes that will be used for the treatment of agricultural land can be evaluated