A multi-objective programming approach to feed ration balancing and nutrient management

Recent technological advances make it possible to deliver feeding strategies that can be tailored to the needs of individual pigs in order to optimise the allocation of nutrient resources and contribute toward reducing excess nutrient excretion. However, these efforts are currently hampered by the challenges associated with: (1) estimation of unobserved traits from the available data on bodyweight and feed consumption; and (2) characterisation of the distributions and correlations of these unobserved traits to generate accurate estimates of individual level variation among pigs. Here, alternative quantitative approaches to these challenges, based on the principles of inverse modelling and separately inferring individual level distributions within a Bayesian context were developed and incorporated in a proposed precision feeding modelling framework. The objectives were to: (i) determine the average and distribution of individual traits characterising growth potential and body composition in an empirical population of growing-finishing barrows and gilts; (ii) simulate the growth and excretion of nitrogen and phosphorus of the average pig offered either a commercial two-phase feeding plan, or a precision feeding plan with daily adjustments; and (iii) simulate the growth and excretion of nitrogen and phosphorus across the pig population under two scenarios: a two-phase feeding plan formulated to meet the nutrient requirements of the average pig or a precision feeding plan with daily adjustments for each and every animal in the population. The distributions of mature bodyweight and ratio of lipid to protein weights at maturity had median (IQR) values of 203 (47.8) kg and 2.23 (0.814) kg/kg, respectively; these estimates were obtained without any prior assumptions concerning correlations between the traits. Overall, it was found that a proposed precision feeding strategy could result in considerable reductions in excretion of nitrogen and phosphorus (average pig: 8.07 and 9.17% reduction, respectively; heterogenous pig population: 22.5 and 22.9% reduction, respectively) during the growing-finishing period from 35 to 120 kg bodyweight. This precision feeding modelling framework is anticipated to be a starting point toward more accurate estimation of individual level nutrient requirements, with the general aim of improving the economic and environmental sustainability of future pig production systems.

Information technology (IT) is defined as the obtainment, procedure, storage and propagation of sounding, drawing, and textual information by combining microelectronics-based computing and telecommunications. Nowadays, IT is starting to spread further from the conventional personal computer and network technologies to integrations of other fields of technology such as the use of cell phones, televisions, automobiles, etc. In other words, IT has penetrated in daily life of human beings and become one part of the whole society. The importance of IT has become momentous. Therefore, to understand the performance of efficiency and productivity of the IT firms is critical for managers as well as for personal investors. Until now, there are very few researches tried to analyze final performance of the IT firms. As a result, this research intends to use traditional Data Envelopment Analysis (DEA) CCR or BCC models to evaluate the performance of IT firms. The Decision Making Units (DMUs) on this research are chosen from IT firms in S&P 500. However, the traditional DEA models are not fair models from the aspect of improper weight derivations. Thus, this paper intends to analyze the efficiency of IT firms in S&P 500 efficiencies by using multiple objective programming (MOP) based Data Envelopment Analysis (DEA). In a MOP based DEA approach, DMUs will be evaluated based on an equal standard and the results will be evaluated more fairly. The world’s leading IT firms in S&P 500 will be evaluated based on publicly available financial reports of the fiscal year 2010. In addition, the newly developed MOP can improve the traditional DEA’s unfair weights problems and benchmark the efficiency of IT firms in S&P 500 correctly. In the empirical study, the MOP based DEA demonstrated that F5 Networks should be the communications equipment companies of IT worthwhile to be invested. In the future, performance evaluation results can be served as foundations for investment strategies definition.KeywordsInformation Technology (IT)Standard and Poor’s 500 indexPerformance EvaluationData Envelopment Analysis (DEA)Multiple Objective Programming (MOP)

Investment programing for multiple objectives rather than simply for the traditional water resource investment objective of increasing the national income has become an important new element in water resources planning in the United States. Reference is made to current multiple objective planning efforts, and the relevant theory is briefly explained. The benefit‐cost ratio appropriate to projects in multiple objective programs is presented, and it is shown how this ratio differs from the ratios required by current federal instructions, which do not allow agencies to reflect accurately the interaction of social preferences and investment opportunities. A change in the federal instructions is recommended.

This study was conducted in order to evaluate the influence of different levels of metabolizable energy and crude protein in diets formulated according to the ideal protein concept with phytase supplementation on performance and nutrient excretion of broilers from 22 to 42 days age. It was used 1,500 Coob lineage broilers at 22 days of age and with initial weight of 833 ± 7g, distributed in completely randomized design in a 3 × 3 + 1 factorial scheme composed of three levels of correct apparent metabolizable energy (2,950; 3,100 and 3,250 kcal/kg), three levels of crude protein (14, 16 and 18%) and a control treatment, totaling ten treatments with six repetitions of 25 birds each. All diets, with the exception of the control, were supplemented with phytase. For determination of excretion of pollutants, it was used 180 broilers from the same lineage at 35 days of age,placed in metabolic cages, with ten treatments each one with six repetitions and three birds per experimental unit. The protein and energy levels in diets containing phytase influenced feed intake, weight gain, feed conversion and excretion of nitrogen, phosphorus, calcium, potassium, copper and zinc by the birds. The corrected apparent metabolizable energy level in the diets for broilers in the studied period must be increased up to 3,250 kcal/kg of metabolizable energy and the levels of crude protein, calcium and phosphorus must be reduced down to 18, 0.70 and 0.31%, respectively, provided that supplemented with amino acids and phytase to improve the performance and to reduce excretion of pollutants by birds.

Biorefined press cake silage as feed source for dairy cows: effect on milk production and composition, rumen fermentation, nitrogen and phosphorus excretion and in vitro methane production

In this paper, we focus on approximating convex compact bodies. For a convex body described as the feasible set in objective space of a multiple objective programme, we show that finding it is equivalent to finding the non-dominated set of a multiple objective programme. This equivalence implies that convex bodies can be approximated using multiple objective optimization algorithms. Therefore, we propose a revised outer approximation algorithm for convex multiple objective programming problems to approximate convex bodies. Finally, we apply the algorithm to solve reachable sets of control systems and use numerical examples to show the effectiveness of the algorithm.

Multiple objective management of public forests based on centralized regional planning is mandated by law in the United States and by development policy in developing countries. Multiple objective programming (MOP) methods have been applied to this problem, but public forests have multiple users whose relative preferences for forest products often cannot be determined, so preference-based goal programming and multiobjective linear programming solutions may be inaccurate or inflexible. The use of noninferior set generating algorithms to solve MOP's encourages more flexible planning by providing a range of possible solutions (the noninferior set), but requires or generates too much information. The NISE (noninferior set estimation) method is an MOP solution technique that uses repeated linear program (LP) solutions to generate an estimate of the true noninferior set, with a known error. The method provides explicit tradeoffs between objectives and requires little interaction with forest users. The NISE method is illustrated for a problem of forest management in Tanzania, and its applicability to centralized forest planning in the United States and developing countries is discussed in the light of legal, political, and institutional constraints. Forest Sci. 32:517-533.

At present, supply chain management has become not only a hot academic research, but also an important respect of the enterprise strategic management. A multi-product, multi-stage integrated supply chain management model was established by multiple-objective programming, which could describe the capability and profit of supply chain members and the coordination operation of supply chain. Then an example was given for testing the effectiveness and feasibility of the model, and the simulation result was compared with that of decentralization supply chain management model. The example shows that multiple objective programming can solve the problem of integrated supply chain management.

In this paper relationships between Pareto points and saddle points are studied in convex and nonconvex multiple objective programming. The analysis is based on partitioning the index sets of objectives and constraints and splitting the original problem into subproblems having a special structure. The results are based on scalarizations of multiple objective programs and related linear and augmented Lagrangian functions. In the nonconvex case, a saddle point characterization of Pareto points is possible under assumptions that guarantee existence of Pareto points and stability conditions of single objective problems. Essentially, these conditions are not stronger than those in analogous results for single objective programming.

Relationships between the Tchebycheff scalarization and the augmented Lagrange multiplier technique are examined in the framework of general multiple objective programs (MOPs). It is shown that under certain conditions the Tchebycheff method can be represented as a quadratic weighted-sums scalarization of the MOP, that is, given weight values in the former, the coefficients of the latter can be found so that the same efficient point is selected. Analysis for concave and linear MOPs is included. Resulting applications in multiple criteria decision making are also discussed.

Freshwater ecosystems are exposed\nto engineered nanoparticles through\nmunicipal and industrial wastewater-effluent discharges and agricultural\nnonpoint source runoff. Because previous work has shown that engineered\nnanoparticles from these sources can accumulate in freshwater algal\nassemblages, we hypothesized that nanoparticles may affect the biology\nof primary consumers by altering the processing of two critical nutrients\nassociated with growth and survivorship, nitrogen and phosphorus.\nWe tested this hypothesis by measuring the excretion rates of nitrogen\nand phosphorus of Physella acuta, a\nubiquitous pulmonate snail that grazes heavily on periphyton, exposed\nto either copper or gold engineered nanoparticles for 6 months in\nan outdoor wetland mesocosm experiment. Chronic nanoparticle exposure\ndoubled nutrient excretion when compared to the control. Gold nanoparticles\nincreased nitrogen and phosphorus excretion rates more than copper\nnanoparticles, but overall, both nanoparticles led to higher consumer\nexcretion, despite contrasting particle stability and physiochemical\nproperties. Snails in mesocosms enriched with nitrogen and phosphorus\nhad overall higher excretion rates than ones in ambient (no nutrients\nadded) mesocosms. Stimulation patterns were different between nitrogen\nand phosphorus excretion, which could have implications for the resulting\nnutrient ratio in the water column. These results suggest that low\nconcentrations of engineered nanoparticles could alter the metabolism\nof consumers and increase consumer-mediated nutrient recycling rates,\npotentially intensifying eutrophication in aquatic systems, for example,\nthe increased persistence of algal blooms as observed in our mesocosm\nexperiment.

We look at the environmental impact of formulating diets for an animal production system, namely the case of growing pigs. The classic approach in animal production is to use a growth model based on the least-cost diet formulation. This optimal diet is generally established by linear programming. Such an approach can lead to adverse environmental effects in the form of nitrogen and phosphorus excretions. Multi-criteria (two and three criteria) models are proposed with the aim of addressing both economic and environmental considerations. We apply the models to two real-life contexts: Quebec (Canada) and France, and make some comparisons. We show that important reductions in nitrogen and phosphorus excretions can be achieved at relatively low costs in both contexts.

This study proposed a multiple objective programming method to solve assortment and packing problems. Instead of using a two-stage method, as proposed by Li & Tsai [7], this study integrated the two stages into a multiple objective program to address assortment problems in one application. Moreover, this method could be extended to solve packing problems containing fewer 0-1 variables, thus, compared with Li et al. [8] the performance time of the proposed method could be decreased. The numerical examples showed that the proposed method is more efficient than Li & Tsai's [7], and Li et al.'s approaches [8].

In this paper, we propose a new interactive procedure for solving multiple objective programming problems. Based upon feed-forward artificial neural networks (FFANNs), the method is called the Interactive FFANN Procedure. In the procedure, the decision maker articulates preference information over representative samples from the nondominated set either by assigning preference “values” to the sample solutions or by making pairwise comparisons in a fashion similar to that in the Analytic Hierarchy Process. With this information, a FFANN is trained to represent the decision maker's preference structure. Then, using the FFANN, an optimization problem is solved to search for improved solutions. An example is given to illustrate the Interactive FFANN Procedure. Also, the procedure is compared computationally with the Tchebycheff Method (Steuer and Choo [Steuer, R. E., E.-U. Choo. 1983. An interactive weighted Tchebycheff procedure for multiple objective programming. Math. Programming 26(1) 326–344.]). The computational results indicate that the Interactive FFANN Procedure produces good solutions and is robust with regard to the neural network architecture.

Interdependence in fuzzy multiple objective programming