• Title/Summary/Keyword: Production optimization

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The Development of Production Simulation Methodology by Optimization Technique and It's Application to Utility Expansion Planning (최적화 기법에 의한 발전시뮬레이션 방법론의 개발 및 전원확충계획 문제에의 적용)

  • Song, K.Y.;Oh, K.H.;Kim, Y.H.;Cha, J.M.
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.793-796
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    • 1996
  • This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

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Enhanced Antibiotic Production by Streptomyces sindenensis Using Artificial Neural Networks Coupled with Genetic Algorithm and Nelder-Mead Downhill Simplex

  • Tripathi, C.K.M.;Khan, Mahvish;Praveen, Vandana;Khan, Saif;Srivastava, Akanksha
    • Journal of Microbiology and Biotechnology
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    • v.22 no.7
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    • pp.939-946
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    • 2012
  • Antibiotic production with Streptomyces sindenensis MTCC 8122 was optimized under submerged fermentation conditions by artificial neural network (ANN) coupled with genetic algorithm (GA) and Nelder-Mead downhill simplex (NMDS). Feed forward back-propagation ANN was trained to establish the mathematical relationship among the medium components and length of incubation period for achieving maximum antibiotic yield. The optimization strategy involved growing the culture with varying concentrations of various medium components for different incubation periods. Under non-optimized condition, antibiotic production was found to be $95{\mu}g/ml$, which nearly doubled ($176{\mu}g/ml$) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production ($197{\mu}g/ml$) was obtained by cultivating the cells with (g/l) fructose 2.7602, $MgSO_4$ 1.2369, $(NH_4)_2PO_4$ 0.2742, DL-threonine 3.069%, and soyabean meal 1.952%, for 9.8531 days of incubation, which was roughly 12% higher than the yield obtained by ANN coupled with GA under the same conditions.

Algorithm for Profit per Cost Ratio of Product Portfolio Problem (제품 포트폴리오 문제의 원가 이익률 알고리즘)

  • Sang-Un Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.3
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    • pp.139-143
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    • 2023
  • The product portfolio problem(PPP) is an optimization problem that determines the production quantity of a particular product to obtain the maximum profit among the n products. Linear programming(LP) is known as the only way to solve this optimization problem. The linear programming method is a problem that optimizes n linear functions and uses LINGO or Excel solver. This paper proposes a simple algorithm that uses CPR, a product cost-profit ratio, to sort in CPR descending order and then determines the maximum allowed production quantity by hand as the actual production quantity. As a result of applying the proposed algorithm to six experimental data, it was shown that more accurate results can be obtained compared to the linear programming method.

Improved FMM for well locations optimization in in-situ leaching areas of sandstone uranium mines

  • Mingtao Jia;Bosheng Luo;Fang Lu;YiHan Yang;Meifang Chen;Chuanfei Zhang;Qi Xu
    • Nuclear Engineering and Technology
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    • v.56 no.9
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    • pp.3750-3757
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    • 2024
  • Rapidly obtaining the coverage characteristics of leaching solution in In-situ Leaching Area of Sandstone Uranium Mines is a necessary condition for optimizing well locations reasonably. In the presented study, the improved algorithm of the Fast Marching Method (FMM) was studied for rapidly solving coverage characteristics to replace the groundwater numerical simulator. First, the effectiveness of the FMM was verified by simulating diffusion characteristics of the leaching solution in In-situ Leaching Area. Second, based on the radial flow pressure equation and the interaction mechanism of the front diffusion of production and injection well flow field, an improved FMM which is suitable for In-situ Leaching Mining, was developed to achieve the co-simulation of production and injection well. Finally, the improved algorithm was applied to engineering practice to guide the design and production. The results show that the improved algorithm can efficiently solve the coverage characteristics of leaching solution, which is consistent with those obtained from traditional numerical simulators. In engineering practice, the improved FMM can be used to rapidly analyze the leaching process, delineate Leaching Blind Spots, and evaluate the rationality of well pattern layout. Furthermore, it can help to achieve iterative optimization and rapid decision-making of production and injection well locations under largescale mining area models.

Optimization of Quantity Allocation using Integer Linear Programming in Shipbuilding Industry (정수 선형 최적화를 이용한 조선해양 의장품 제작 물량 할당에 관한 연구)

  • Park, JungGoo;Kim, MinGyu
    • Journal of the Society of Naval Architects of Korea
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    • v.57 no.1
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    • pp.45-51
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    • 2020
  • In this study, we developed an allocation optimization system for supply chain management in the shipbuilding and offshore construction industry. Supply chain operation is a way of operating manufacturing company responsible for the procurement of outfitting parts. The method about how to allocate the manufacturing volume to each partner company includes important decisions. According to the allocation method, the stability of the material supplied to the final installation process is guaranteed. We improved the allocation method that was previously decided by the person in charge. Based on the optimization engine, a system is developed that can automatically allocate the production volume. For optimization model configuration, factors affecting the volume allocation were analyzed and modeled as constraint factors. A target function is defined to minimize the difference in the load variance of each partner company. In order to use the same type of volume allocation engine for various outfitting products, the amount of work done by the partner company was standardized. We developed an engine that can allocate the same production load of each production partner. Using this engine, the operating system was developed and applied to the actual offshore project. It has been confirmed that the work load variance of suppliers can be maintained uniformly using the optimization engine rather than manual method. By this system, we stabilize the manufacturing process of partner suppliers.

A modeling of manufacturing system and a model analysis by a SIMAN language (생산공정의 모델링과 SIMAN 언어에 의한 모델분석)

  • 이만형;김경천;한성현
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.300-306
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    • 1987
  • This paper deals with a modeling of manufacturing system and a model analysis by a SIMAN language. A flow of production process is analyzed, and a mathematical model on the basis of the analyzed data is simulated by a SIMAN language. An object of this study is to achieve an optimization of production a reduction of cost, and an improvement of quality by a applicable line-balancing technique and an optimization technique in a real factor induced an analysis and synthesis of the result of simulation.

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OPTIMIZATION OF CULTURE CONDITIONS FOR PRODUCTION OF PNEUMOCOCCAL CAPSULAR POLYSACCHARIDE TYPE I

  • Kim, S.N.;K.K. Min;Kim, S.H.;Park, I.H.;Lee, S.H.;S.N. Pyo;D.K. Rhee
    • Proceedings of the Korean Society of Applied Pharmacology
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    • 1996.04a
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    • pp.186-186
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    • 1996
  • Streptococcus pneumoniae (pneumococcus), the most common cause of bacterial pneumonia, has an ample polysaccharide(PS) capsule that is highly antigenic and is the source of PS vaccine. This investigation was undertaken to optimize the culture conditions for the production of capsular PS by type 1 pneumococcus. Among several culture media, brain heart infusion (BHI) and Casitone based media were found to support luxuriant growth of pneumococcus type 1 at the same level. Because BHI medium is rather expensive and more complex than the Casitone based media, the Casitone based media was used to study optimization of the culture condition. The phase of growth which accomodated maximum PS production was logarithmic phase. Concentrations of glucose greater than 0.2% did not enhance growth or PS production. Substitution of nitrogen sources with other resources or supplemention of various concentrations of metal ion (with the exception of calcium ion) had adverse effects on growth and PS production. On the other hand, low level aeration was beneficial for increased PS production. Addition of 3 mg/I concentration of methionine, phenylalanine, and threonine were found to enhance growth and PS production. The synergistic effect of all the favorable conditions observed in pneumococcal growth assays provided a two-fold cumulative increase in capsular PS production.

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Statistical Optimization of Production Medium for Enhanced Production of Succinic Acid Produced by Anaerobic Fermentations of Actinobacillus succinogenes (Actinobacillus succinogenes의 혐기성배양에 의해 생합성 되는 숙신산의 생산성 향상을 위한 통계적 생산배지 최적화)

  • Park, Sang-Min;Chun, Gie-Taek
    • KSBB Journal
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    • v.29 no.3
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    • pp.165-178
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    • 2014
  • Statistical medium optimization has been carried out for the production of succinic acid in anaerobic fermentations of Actinobacillus succinogenes. Succinic acid utilized as a precursor of many industrially important chemicals is a fourcarbon dicarboxylic acid, biosynthesized as one of the fermentation products of anaerobic metabolism by A. succinogenes. Through OFAT (one factor at a time) experiments, corn steep liquor (CSL), a very cheap agricultural byproduct, was found to have significant effects on enhanced production of succinic acid, when supplemented along with yeast extract. Hence, using these factors including glucose as a carbon/energy source, interactive effects were investigated through $2^n$ full factorial design (FFD) experiments, showing that the concentration of each component (i.e., glucose, yeast extract and CSL) should be higher. Further statistical experiments were conducted along the steepest ascent path, followed by response surface method (RSM) in order to find out optimal concentrations of each constituent. Consequently, optimized concentrations of glucose, yeast extract and CSL were observed to be 180 g/L, 15.08 g/L and 20.75 g/L respectively (10 g/L of $NaHCO_3$ and 100 g/L of $MgCO_3$ to be supplemented as bicarbonate suppliers), with the estimated production level of succinic acid to be 92.9 g/L (about 3.5 fold higher productivity as compared to the initial medium). Notably, the RSM-estimated production level was almost similar to the amount of succinic acid (92.9 g/L vs. 89.1 g/L) produced through the actual fermentation process performed using the statistically optimized production medium.

Optimization of Medium for Lipase Production from Zygosaccharomyces mellis SG1.2 Using Statistical Experiment Design

  • Pramitasari, Marisa Dian;Ilmi, Miftahul
    • Microbiology and Biotechnology Letters
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    • v.49 no.3
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    • pp.337-345
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    • 2021
  • Lipase (triacylglycerol lipase, EC 3.1.1.3) is an enzyme capable of hydrolyzing triacylglycerol, to produce fatty acids and glycerol and reverse the reaction of triacylglycerol synthesis from fatty acids and glycerol through transesterification. Applications of lipase are quite widespread in the industrial sector, including in the detergent, paper, dairy, and food industries, as well as for biodiesel synthesis. Lipases by yeasts have attracted industrial attention because of their fast production times and high stability. In a previous study, a lipase-producing yeast isolate was identified as Zygosaccharomyces mellis SG1.2 and had a productivity of 24.56 U/mg of biomass. This productivity value has the potential to be a new source of lipase, besides Yarrowia lypolitica which has been known as a lipase producer with a productivity of 0.758 U/mg. Lipase production by Z. mellis SG1.2 needs to be increased by optimizing the production medium. The aims of this study were to determine the significant component of the medium for lipase production and methods to increase lipase production using the optimum medium. The two methods used for the statistical optimization of production medium were Taguchi and RSM (Response Surface Methodology). The data obtained were analyzed using Minitab 18 and SPSS 23 software. The most significant factors which affected lipase productivity were olive oil and peptones. The optimum medium composition consisted of 1.02% olive oil, 2.19% peptone, 0.05% MgSO4·7H2O, 0.05% KCl, and 0.2% K2HPO4. The optimum medium was able to increase the lipase productivity of Z. mellis SG1.2 to 1.8-fold times the productivity before optimization.

Isolation of Chitinolytic Bacteria from the Viscera of Korean Bony Fishes and Optimization of the Enzyme Production

  • Lee Jung-Suck;Joo Dong-Sik;Cho Soon-Yeong;Cho Man-Gi;Lee Eung-Ho
    • Fisheries and Aquatic Sciences
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    • v.2 no.1
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    • pp.105-111
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    • 1999
  • In order to produce functional chitin oligosaccharides, a chitinolytic bacterium was newly screened from the viscera of Korean bony fishes, and identified as Bacillus sp. LJ-25. For the production of chitinolytic enzymes, $1.0\%$ nutrient broth and $0.3\%$ colloidal chitin were used as nitrogen and carbon source, respectively. The optimal temperature, initial pH and concentration of NaCl for the enzyme production by Bacillus sp. LJ-25 were $30^{\circ}C$ 6.5-7.0 and $1.0\%$, respectively. The enzyme activity of Bacillus sp. LJ-25 increased until the incubation time of 168 hr, followed by a decrease in activity.

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