SAA Method Research Articles

Analysis of the Physical Quality of Chicken Eggs Fed with Added Calcium Fish Oil by Spectroscopic Method

This research was carried out with the aim of improving the physical quality, chicken eggs and the effect of optimum levels by adding fish oil calcium to the feed. The method was a completely randomized design with 4 treatments and 4 replications, namely P0 as control; P1 added fish oil 0.2% in feed; P2 added fish oil 0.4% in feed; P3 was added with 0.6% fish oil in the feed, each study unit used 10 chickens; the total chickens in the study were 160 chickens. After 30 days of the treatment, then the analysis was carried out every week for six weeks using an electric screw micrometer to measure the thickness of the eggshell, the LIBS method used to determine the hardness index, the SAA method used to measure the surface area and pore size. Barrett-Joiner_Halenda method used to determine the pore diameter of the eggshell, and the AAS method used to determine the concentration of calcium. The results showed that the addition of calcium from fish oil in general can improve physical quality of the eggshell compared to controls. The optimum level of fish oil calcium in the feed to produce the best physical quality is 0.4%.

Composite Anderson acceleration method with two window sizes and optimized damping

AbstractIn this article, we propose and analyze a set of fully nonstationary Anderson acceleration (AA) algorithms with two window sizes and optimized damping. Although AA has been used for decades to speed up nonlinear solvers in many applications, most authors are simply using and analyzing the stationary version of AA (sAA) with fixed window size and a constant damping factor. The behavior and potential of the nonstationary version of AA methods remain an open question. Most efficient linear solvers however use composable algorithmic components. Similar ideas can be used for AA to solve nonlinear systems. Thus in the present work, to develop nonstationary AA algorithms, we first propose a systematic way to dynamically alternate the window size by the multiplicative composite combination, which means we apply sAA() in the outer loop and apply sAA() in the inner loop. By doing this, significant gains can be achieved. Second, to make AA to be a fully nonstationary algorithm, we need to combine these strategies with our recent work on the nonstationary AA algorithm with optimized damping (AAoptD), which is another important direction of producing nonstationary AA and nice performance gains have been observed. Moreover, we also investigate the rate of convergence of these nonstationary AA methods under suitable assumptions. Finally, our numerical results show that some of these proposed nonstationary AA algorithms converge faster than the stationary sAA method and they may significantly reduce the storage and time to find the solution in many cases.

LPG leakage and explosion accident analysis based on a new SAA method

The petrochemical industry has inherently high safety risks. On 5th June 2017, a liquefied petroleum gas tanker in the storage and transportation department of Linyi Jinyu Petrochemical Co., Ltd. leaked during unloading, causing a major explosion and fire. Ten people were killed and nine were injured. To prevent the recurrence of similar accidents, a retrospective accident analysis was conducted using the system accident analysis method known as ‘24Model’. This analysis proved the coupling relationship between accident causes involving multiple organisations and multiple factors. The analysis results show that the five modules of maintenance and design, that is, loading and unloading valves, emergency training, management of subsidiaries and contractors, multi-level supervision, and task arrangement need to be checked from top to bottom by relevant organisations.In order to verify the reliability of 24Model analysis results, three SAA methods, namely STAMP, FRAM, AcciMap, were used to analyse the accident, and results obtained by the four methods were evaluated qualitatively and quantitatively. The results show that the output of 24Model is reliable and has a more understandable framework, which can be used as reference for the development of other linear accident cause models and application of system accident analysis methods to real applications.

Variable sample size method for equality constrained optimization problems

An equality constrained optimization problem with a deterministic objective function and constraints in the form of mathematical expectation is considered. The constraints are transformed into the Sample Average Approximation form resulting in deterministic problem. A method which combines a variable sample size procedure with line search is applied to a penalty reformulation. The method generates a sequence that converges towards first-order critical points. The final stage of the optimization procedure employs the full sample and the SAA problem is eventually solved with significantly smaller cost. Preliminary numerical results show that the proposed method can produce significant savings compared to SAA method and some heuristic sample update counterparts while generating a solution of the same quality.

Study of M-stationarity and strong stationarity for a class of SMPCC problems via SAA Method

In this article my main aim is to analyze the relative importance of M-stationarity concept over strong stationarity of one stage stochastic mathematical programming problems with complementarity constraints (SMPCC, in short). We establish the consistency of M-stationary multipliers when the SMPCC problem is approximated through the sample average approximation (SAA, for short) method, under the assumption of SMPCC-NNAMCQ. On contrary, strong stationary multipliers are not consistent even in presence of SMPCC-LICQ.

Smoothing and SAA method for stochastic programming problems with non-smooth objective and constraints

We consider a stochastic non-smooth programming problem with equality, inequality and abstract constraints, which is a generalization of the problem studied by Xu and Zhang (Math Program 119:371---401, 2009) where only an abstract constraint is considered. We employ a smoothing technique to deal with the non-smoothness and use the sample average approximation techniques to cope with the mathematical expectations. Then, we investigate the convergence properties of the approximation problems. We further apply the approach to solve the stochastic mathematical programs with equilibrium constraints. In addition, we give an illustrative example in economics to show the applicability of proposed approach.

Pretreatment of Oil Palm Empty Fruit Fiber (OPEFB) with Aquaeous Ammonia for High Production of Sugar

Corncob Oil Palm Empty Fruit Bunch (OPEFB) is an agricultural residue that has the potential to become a good source for renewable feedstock for production of sugar. This work evaluated the effectiveness of aqueous ammonia as pretreatment at low (soaking, SAA) and elevated temperature (Pressurized Chamber) to deconstruct the lignocellulosic feedstock, prior to enzymatic hydrolysis. The ammonia pretreatments were compared against the standard NaOH method. The best tested Pressurized Chamber method conditions were at 100°C with 3 hour retention time, 12.5% Ammonium hydroxide and 1:30 solid loading. The digestibility of the feedstock is determined with enzymatic hydrolysis using Cellic Ctech2 and Cellic Htech2. The sugars produced by Pressurized Chamber method within 24 hour of enzyme hydrolysis are similar to that produced by NaOH method which is 439.90mg/ml and 351.61mg/ml, respectively. Compared with optimum SAA method (24 hour, 6.25% of ammonium hydroxide at room temperature), Pressurized Chamber method was capable of producing enhanced delignification and higher production of sugar upon hydrolysis. These findings were supported by the disappearance peak at 1732, 1512 and 1243 on Fourier Transform Infrared (FTIR spectrum) of treated OPEFB by Pressurized Chamber method. XRD determination showed reduced crystallinity of OPEFB (37.23%) after treatment by Pressurized Chamber, suggesting higher accessibility toward enzyme hydrolysis. The data obtained suggest that the Pressurized Chamber pre-treatment method are suitable for OPEFB deconstruction to produce high yield of sugar.

A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem

Abstract We present a novel hybrid method, swarm intelligence based sample average approximation (SIBSAA), for solving the capacitated reliable facility location problem (CRFLP). The CRFLP extends the well-known capacitated fixed-cost facility problem by accounting for the unreliability of facilities. The standard SAA procedure, while effectively used in many applications, can lead to poor solution quality if the selected sample sizes are not sufficiently large. With larger sample sizes, however, the SAA method is not practical due to the significant computational effort required. The proposed SIBSAA method addresses this limitation by using smaller samples and repetitively applying the SAA method while injecting social learning in the solution process inspired by the swarm intelligence of particle swarm optimization. We report on experimental study results showing that the SIBSAA improves the computational efficiency significantly while attaining same or better solution quality than the SAA method.

Production of new haemostatic materials by deposition of dispersed proteins onto porous matrices using supercritical carbon dioxide

The main features of microparticle formation from protein substances (trypsin, lysozyme) using supercritical fluids (SAA method) are studied. Optical and scanning electron microscopies are employed to examine the morphology of the particles. The size distribution of the particles is studied using a cascade impactor. A method of deposition of particles onto Collachit-G haemostatic material is developed.

Penalty-based SAA method of stochastic nonlinear complementarity problems

We consider a class of stochastic nonlinear complementarityproblems. We first formulate the stochastic complementarity problemas a stochastic programming model. Based on this reformulation, wepropose a penalty-based sample average approximation (in short, SAA) method forstochastic complementarity problem and prove its convergence.Finally, we report some numerical test results to show theefficiency of our method.

Sequential optimization algorithms for complex extended construction projects

Theoretical and practical results indicate that the SAA method can be efficiently applied for the solution of road construction optimization problems with allowance for construction dynamics.