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Journal articles on the topic 'Scenario-based programming'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Alexandron, Giora, Michal Armoni, Michal Gordon, and David Harel. "Scenario-Based Programming, Usability-Oriented Perception." ACM Transactions on Computing Education 14, no. 3 (2014): 1–23. http://dx.doi.org/10.1145/2648814.

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Tarim, S. Armagan, Suresh Manandhar, and Toby Walsh. "Stochastic Constraint Programming: A Scenario-Based Approach." Constraints 11, no. 1 (2006): 53–80. http://dx.doi.org/10.1007/s10601-006-6849-7.

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3

Cao, M. F. "Scenario-Based Methods for Interval Linear Programming Problems." Journal of Environmental Informatics 17, no. 2 (2011): 65–74. http://dx.doi.org/10.3808/jei.201100188.

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4

Li, Zhuangzhi, and Zukui Li. "Linear programming-based scenario reduction using transportation distance." Computers & Chemical Engineering 88 (May 2016): 50–58. http://dx.doi.org/10.1016/j.compchemeng.2016.02.005.

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5

Li, Xuandong, Minxue Pan, Lei Bu, Linzhang Wang, and Jianhua Zhao. "Timing analysis of scenario-based specifications using linear programming." Software Testing, Verification and Reliability 22, no. 2 (2012): 121–43. http://dx.doi.org/10.1002/stv.434.

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6

Yuan, Yifei, Dong Lin, Siri Anil, et al. "NetEgg: A Scenario-Based Programming Toolkit for SDN Policies." IEEE/ACM Transactions on Networking 26, no. 5 (2018): 2104–17. http://dx.doi.org/10.1109/tnet.2018.2861919.

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7

JI, XIAODONG, XIUJUAN ZHAO, and XIULI CHAO. "A NOVEL METHOD FOR MULTISTAGE SCENARIO GENERATION BASED ON CLUSTER ANALYSIS." International Journal of Information Technology & Decision Making 05, no. 03 (2006): 513–30. http://dx.doi.org/10.1142/s0219622006002106.

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Based on cluster analysis, a novel method is introduced in this paper to generate multistage scenarios. A linear programming model is proposed to exclude the arbitrage opportunity by appending a scenario to the generated scenario set. By means of a cited stochastic linear goal programming portfolio model, a case is given to exhibit the virtues of this scenario generation approach.

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Golpîra, Hêriş. "A Scenario Based Stochastic Time-Cost-Quality Trade-Off model for Project Scheduling Problem." International Journal of Management Science and Business Administration 2, no. 5 (2014): 7–12. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.25.1001.

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This paper formulates a new time–cost trade-off problem under some uncertainties for a multi-phase project. To do this, a new approach is proposed based on goal programming in compliance with scenario-based stochastic optimization formulation. To the best of our knowledge, this problem has not been extensively treated in the literature. Computational results show the applicability and usefulness of the proposed method.

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9

Sharifi, Mohammadreza, and Roy H. Kwon. "Performance-based contract design under cost uncertainty: A scenario-based bilevel programming approach." Engineering Economist 63, no. 4 (2018): 291–318. http://dx.doi.org/10.1080/0013791x.2018.1467990.

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Li, He Peng, Chuan Zhi Zang, Peng Zeng, Hai Bin Yu, and Zhong Wen Li. "Scenario-Based Stochastic Programming Strategy for Microgrid Energy Scheduling Considering Uncertainties." Applied Mechanics and Materials 672-674 (October 2014): 1322–28. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1322.

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The inherent random and intermittence of the renewable energy resources pose a huge challenge to the Microgrid (MG) energy management systems (EMS). In order to mitigate the effects of uncertainties, we propose a novel two-stage stochastic programming model for the energy scheduling optimization by considering the uncertainties in solar and wind generation, and the plug-in electric vehicles (EV). The random nature of uncertainty is characterized by a scenarios generation approach based on autoregressive moving average (ARMA) model according to probability density function of each random variable. By use of the strategy of scenarios simulation, the stochastic problem is decomposed into the deterministic equivalent problem. The firefly algorithm (FA) is used to solve the equivalent model. The effectiveness and robust of proposed stochastic energy scheduling optimization strategy for MG is valid by comparison with the simulation results of deterministic method.

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11

Chen, Zhi-Long, Shanling Li, and Devanath Tirupati. "A scenario-based stochastic programming approach for technology and capacity planning." Computers & Operations Research 29, no. 7 (2002): 781–806. http://dx.doi.org/10.1016/s0305-0548(00)00076-9.

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12

Mitra, Sovan, and Tong Ji. "Optimisation of stochastic programming by hidden Markov modelling based scenario generation." International Journal of Mathematics in Operational Research 2, no. 4 (2010): 436. http://dx.doi.org/10.1504/ijmor.2010.033439.

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13

Jayaraman, Raja, Cinzia Colapinto, Danilo Liuzzi, and Davide La Torre. "Planning sustainable development through a scenario-based stochastic goal programming model." Operational Research 17, no. 3 (2016): 789–805. http://dx.doi.org/10.1007/s12351-016-0239-8.

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14

Li, Y. P., G. H. Huang, and X. Chen. "Multistage scenario-based interval-stochastic programming for planning water resources allocation." Stochastic Environmental Research and Risk Assessment 23, no. 6 (2008): 781–92. http://dx.doi.org/10.1007/s00477-008-0258-y.

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15

Papavasiliou, A., S. S. Oren, and R. P. O'Neill. "Reserve Requirements for Wind Power Integration: A Scenario-Based Stochastic Programming Framework." IEEE Transactions on Power Systems 26, no. 4 (2011): 2197–206. http://dx.doi.org/10.1109/tpwrs.2011.2121095.

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16

Barak, D., D. Harel, and R. Marelly. "InterPlay: Horizontal Scale-Up and Transition to Design in Scenario-Based Programming." IEEE Transactions on Software Engineering 32, no. 7 (2006): 467–85. http://dx.doi.org/10.1109/tse.2006.67.

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17

Ji, Xiaodong, Shushang Zhu, Shouyang Wang, and Shuzhong Zhang. "A stochastic linear goal programming approach to multistage portfolio management based on scenario generation via linear programming." IIE Transactions 37, no. 10 (2005): 957–69. http://dx.doi.org/10.1080/07408170591008082.

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18

Shi, Zhong Guo. "A Fuzzy Model of Scenario Planning Based on the Credibility Theory and Fuzzy Programming." Advanced Materials Research 328-330 (September 2011): 2423–26. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.2423.

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Uncertainty, complexity and paradigm shift are three challenges that are inherent in emerging technologies. Scenarios provide background for decision-making by clarifying possible paths of emerging technologies. Based on the analysis of three basic stages of empirical scenario construction, i.e. analysis phase, subsystem analysis phase and syntheses phase, credibility theory and fuzzy programming are introduced to dissolve scenario planning problems. This paper adopt such research road as (1) measurement of factors’ credibility, (2) analysis of pairwise factors’ compatibility, (3) eliminate incompatible scenarios through pruning rules, and (4) choice of scenarios through fuzzy programming. And then, the choice of scenarios can be conducted by expected value model. In the end, the further research fields are also discussed.

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Kunwar, Sundar. "Scenario Based Requirement Engineering (SBRE) in eXtreme Programming (XP) through Agile Modelling (AM)." SCITECH Nepal 13, no. 1 (2018): 9–15. http://dx.doi.org/10.3126/scitech.v13i1.23496.

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Software development methodologies have been enhancing significantly all the time and have drawn the attention of software professionals from past few years. The software development methodologies are expanding rigorously with wide range of diverse fields and have become more complex demanding the agility to rapidly changing needs of the customers. As a result, agile software development methodologies have evolved and gaining popularity day by day. Agile software development methodologies have come up with modifications demanded in traditional software development process to make them faster; more flexible, light weighted and productive. Extreme Programming (XP) is one of the well-known agile software development methodologies and is driven by a set of values including simplicity, communication, feedback and courage. Planning game, very short release stories and test first coding are some interesting extreme practices of XP; however, it is criticized for some deficiencies like light weight requirement, onsite customer, pair programming and so on. The study has only focused on only one of the most criticized extreme practice-lightweight requirement and has followed agile modelling approach to make improvement on requirement engineering process in XP. Requirements are the user stories that consist of a few sentences (1-3 sentences) written on an index card which describes the functionality given by single onsite customer in XP. There is lack of analysis of stakeholders and their roles in requirement process. Therefore, it is very difficult to know the specific requirements of the specific stakeholder in XP. This means that the requirement engineering process is incomplete in XP. This may result high chances of providing deficient requirements. Agile Modelling (AM) is the chaordic practice based methodology for effective modelling. The interesting part of AM is that it does not tell how to model, but tells about how to be effective as modellers. A Scenario Based Requirement Engineering (SERE) is proposed using AM as alternative to light weighted requirement which one of the most criticized extreme practice of XP. SERE is the implemented description of techniques that helps to understand the task related activities and also facilitates communication among stakeholders and experts. Stakeholders are analysed for understanding a system by identifying the stakeholders in the system and assessing their respective requirements and influence on the system. This will help to get better requirements for system development, but still needs to be validated.

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송창훈 and 박석봉. "A Two-Stage Scenario-Based Stochastic Programming Approach To Pre-Positioning Emergency Supplies." Korean Journal of Military Art and Science 68, no. 2 (2012): 97–109. http://dx.doi.org/10.31066/kjmas.2012.68.2.005.

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21

Cui, LiYing, Soundar Kumara, and Dongwon Lee. "Scenario Analysis of Web Service Composition based on Multi-Criteria Mathematical Goal Programming." Service Science 3, no. 4 (2011): 280–303. http://dx.doi.org/10.1287/serv.3.4.280.

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22

Meng, Qiang, and Tingsong Wang. "A scenario-based dynamic programming model for multi-period liner ship fleet planning." Transportation Research Part E: Logistics and Transportation Review 47, no. 4 (2011): 401–13. http://dx.doi.org/10.1016/j.tre.2010.12.005.

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23

Watkins, D. W., D. C. McKinney, L. S. Lasdon, S. S. Nielsen, and Q. W. Martin. "A scenario-based stochastic programming model for water supplies from the highland lakes." International Transactions in Operational Research 7, no. 3 (2000): 211–30. http://dx.doi.org/10.1111/j.1475-3995.2000.tb00195.x.

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24

Wang, Chunhui, Wei Zhang, Haiyan Zhao, and Zhi Jin. "Towards a fictional collective programming scenario: an approach based on the EIF loop." Empirical Software Engineering 25, no. 5 (2020): 3671–710. http://dx.doi.org/10.1007/s10664-020-09850-7.

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25

Mohd Noh, Norshela, Arifah Bahar, and Zaitul Marlizawati Zainuddin. "Scenario Based Two-Stage Stochastic Programming Approach for the Midterm Production Planning of Oil Refinery." MATEMATIKA 34, no. 3 (2018): 45–55. http://dx.doi.org/10.11113/matematika.v34.n3.1138.

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Recently, oil refining industry is facing with lower profit margin due to uncertainty. This causes oil refinery to include stochastic optimization in making a decision to maximize the profit. In the past, deterministic linear programming approach is widely used in oil refinery optimization problems. However, due to volatility and unpredictability of oil prices in the past ten years, deterministic model might not be able to predict the reality of the situation as it does not take into account the uncertainties thus, leads to non-optimal solution. Therefore, this study will develop two-stage stochastic linear programming for the midterm production planning of oil refinery to handle oil price volatility. Geometric Brownian motion (GBM) is used to describe uncertainties in crude oil price, petroleum product prices, and demand for petroleum products. This model generates the future realization of the price and demands with scenario tree based on the statistical specification of GBM using method of moment as input to the stochastic programming. The model developed in this paper was tested for Malaysia oil refinery data. The result of stochastic approach indicates that the model gives better prediction of profit margin.

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26

Rebennack, Steffen. "Combining sampling-based and scenario-based nested Benders decomposition methods: application to stochastic dual dynamic programming." Mathematical Programming 156, no. 1-2 (2015): 343–89. http://dx.doi.org/10.1007/s10107-015-0884-3.

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27

Zhang, Shu Teng, Ya Jie Dou, and Qing Song Zhao. "Evaluation of Capability of Weapon System of Systems Based on Multi-Scenario." Advanced Materials Research 926-930 (May 2014): 3806–11. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3806.

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The capability planning is a fundamental task when designing a Weapon System of Systems (WSOS). Uncertainties exist when building WSOS. It is difficult to select the most appropriate alternatives under the background of system operations. The programming of capability of WSOS is a multi-criteria decision-making problem. To resolve this problem, a scenario-based multi-criteria decision-making methodology is proposed. Scenario describes the future situation may occur, and also presents the uncertainty of reality. In this paper, scenario was modeled by the key variables in which experts and stakeholders are interested. TOPSIS was also improved based on multiple scenarios. Finally, the method is validated by an example of armored weapon systems.

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28

Nourani, Vahid, Mehdi Komasi, and Mohamad Taghi Alami. "Geomorphology-based genetic programming approach for rainfall–runoff modeling." Journal of Hydroinformatics 15, no. 2 (2012): 427–45. http://dx.doi.org/10.2166/hydro.2012.113.

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Nowadays, artificial intelligence approaches such as artificial neural network (ANN) as a self-learn non-linear simulator and genetic programming (GP) as a tool for function approximations are widely used for rainfall–runoff modeling. Both approaches are usually created based on temporal characteristics of the process. Hence, the motivation to present a comprehensive model which also employs the watershed geomorphological features as spatial data. In this paper, two different scenarios, separated and integrated geomorphological GP (GGP) modeling based on observed time series and spatially varying geomorphological parameters, were presented for rainfall–runoff modeling of the Eel River watershed. In the first scenario, the model could present a good insight into the watershed hydrologic operation via GGP formulation. In the second scenario, an integrated model was proposed to predict runoff in stations with lack of data or any point within the watershed due to employing the spatially variable geomorphic parameters and rainfall time series of the sub-basins as the inputs. This ability of the integrated model for the spatiotemporal modeling of the process was examined through the cross-validation technique. The results of this research demonstrate the efficiency of the proposed approaches due to taking advantage of geomorphological features of the watershed.

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29

Wang, Zong Wu, Guo He Huang, and Xiao Kun Li. "Regional Power Planning Optimization Model and Scenario Analysis Considering the Environmental Cost." Advanced Materials Research 805-806 (September 2013): 1122–28. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.1122.

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In this study, a regional power planning optimization model (RPPOM) is developed considering the environmental cost and the restriction of resource and environment, based on interval linear programming and mixed integer linear programming. Model is applied to a case study on the power planning in Henan province, and scenario analysis is conducted. Interval solutions associated with scenario of pollution control have been obtained. They can be used for generating decision alternatives and helping decision makers identify desired power policies for power planning to meet the growth in electricity demand considering the constraints of resources and environment with a minimized system cost. Scenario analysis of environmental pollution control at different levels can also be tackled.

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30

Chung, Shu-Hsing, and Yi-Shu Yang. "A scenario-based stochastic programming model for the control or dummy wafers downgrading problem." Applied Stochastic Models in Business and Industry 25, no. 3 (2009): 263–74. http://dx.doi.org/10.1002/asmb.748.

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31

Chopra, Isha, and Dharmaraja Selvamuthu. "Scenario generation in stochastic programming using principal component analysis based on moment-matching approach." OPSEARCH 57, no. 1 (2019): 190–201. http://dx.doi.org/10.1007/s12597-019-00418-8.

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32

Niknam, Taher, Rasoul Azizipanah-Abarghooee, and Mohammad Rasoul Narimani. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation." Applied Energy 99 (November 2012): 455–70. http://dx.doi.org/10.1016/j.apenergy.2012.04.017.

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33

Margaris, Dionisis, Dimitris Spiliotopoulos, Apostolos Kardiasmenos, and Dimitrios Pantazopoulos. "An integer programming-based algorithm for optimising the WS-BPEL scenario execution adaptation process." International Journal of Web Engineering and Technology 15, no. 3 (2020): 307. http://dx.doi.org/10.1504/ijwet.2020.113068.

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34

Zhang, Pengcheng, Kun Cheng, and Jerry Gao. "Android-SRV: Scenario-Based Runtime Verification of Android Applications." International Journal of Software Engineering and Knowledge Engineering 28, no. 02 (2018): 239–57. http://dx.doi.org/10.1142/s0218194018500080.

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With the wide-spread usage of Android systems, Android applications have become the target of mobile malwares. Therefore, an effective verification approach for Android applications is essential. Runtime verification based on monitors is one of the most promising techniques to check the software’s behaviors. Currently, there are a number of monitoring approaches for Android applications. However, these approaches mainly have two limitations. First, there is no effective mechanism to reduce the load on Android applications caused by monitors. Second, these approaches mainly rely on logic-based specifications, which are complex and not intuitive for being used in practice. In order to address these two limitations, this paper proposes a scenario-based runtime verification approach for Android applications (called Android-SRV). The approach concentrates on providing a dynamic and usable solution for monitoring applications during execution with the help of aspect-oriented programming. It will translate the scenario-based specification (called property sequence charts (PSCs)) into multi-valued automata (MAs), and then generate AspectJ codes from the MA. Finally, these AspectJ codes are weaved into the target system as monitors. Considering the impact of the monitors on performance load in the Android system, the paper proposes local and cloud collaboration mechanisms to reduce the impact. The scenario-based specification is more intuitive than the traditional logic-based specifications. The approach is shown to be an effective means for monitoring Android applications with controlled overload.

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35

Zheng, Xiao Li, Ji Chun Liu, Jia Yi Li, et al. "The Reserve Capacity Model Based on the Idea of Scenario in Power System." Advanced Materials Research 1008-1009 (August 2014): 173–78. http://dx.doi.org/10.4028/www.scientific.net/amr.1008-1009.173.

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According to the impact of the wind power prediction uncertainty on the power system reserve capacity, the idea of scenario is introduced to the stochastic programming model. The method of scenario is used to simulate the uncertainty model of the wind power generation, load and the conventional units. The scenario-reduction methodology is combined to reduce the large scenario set to a simpler one, then the probability statistics on these scenarios is given in order to obtain the probability density of the system power difference, and the expected energy not supplied (EENS) and expected wind waste risk (EWWR) are presented. The reserve capacity is determined by the two aspects, which are the reliability shown by EENS and EWWR, and the economy of reserve capacity cost. Finally, simulations on a ten-unit system are given to demonstrate the method is effective to reduce the cost of reserve and the abandoned wind power in the context of system reliability.

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36

Samimi, Abouzar, and Ahad Kazemi. "Scenario-Based Stochastic Programming for Volt/Var Control in Distribution Systems With Renewable Energy Sources." IETE Technical Review 33, no. 6 (2016): 638–50. http://dx.doi.org/10.1080/02564602.2015.1135088.

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37

Maggioni, Francesca, Florian A. Potra, and Marida Bertocchi. "A scenario-based framework for supply planning under uncertainty: stochastic programming versus robust optimization approaches." Computational Management Science 14, no. 1 (2017): 5–44. http://dx.doi.org/10.1007/s10287-016-0272-3.

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38

Bayliss, Christopher, Geert De Maere, Jason A. D. Atkin, and Marc Paelinck. "A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty." Annals of Operations Research 252, no. 2 (2016): 335–63. http://dx.doi.org/10.1007/s10479-016-2174-8.

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39

Woo, Young-Bin, and Ilkyeong Moon. "Scenario-based stochastic programming for an airline-driven flight rescheduling problem under ground delay programs." Transportation Research Part E: Logistics and Transportation Review 150 (June 2021): 102360. http://dx.doi.org/10.1016/j.tre.2021.102360.

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40

Zhou, Tingting, Ming Li, Xiaoming Mai, Qi Wang, Fang Liu, and Qingquan Li. "Trajectory Generation Model-Based IMM Tracking for Safe Driving in Intersection Scenario." International Journal of Vehicular Technology 2011 (December 23, 2011): 1–8. http://dx.doi.org/10.1155/2011/103696.

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Tracking the actions of vehicles at crossroads and planning safe trajectories will be an effective method to reduce the rate of traffic accident at intersections. It is to resolve the problem of the abrupt change because of the existence of drivers' voluntary choices. In this paper, we make approach of an improved IMM tracking method based on trajectory generation, abstracted by trajectory generation algorithm, to improve this situation. Because of the similarity between human-driving trajectory and programming trajectory which is generated by trajectory-generated algorithm, the improved IMM method performs well in tracking moving vehicles with some sudden changes of its movement. A set of data is collected for experiments when an object vehicle takes a sudden left turn in intersection scenario. To compare the experiment results between IMM method with trajectory generation model and the one without, tracking error of the former decreases by 75% in particular scenario.

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41

Samanta, Gopinath, Tapan Dey, Biswajit Samanta, and Suranjan Sinha. "Stope boundary optimization for an underground copper deposit using mixed integer linear programming based algorithm." Journal of Mines, Metals and Fuels 69, no. 3 (2021): 73. http://dx.doi.org/10.18311/jmmf/2021/27781.

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Optimal ore body boundary and production area geometry (Stope) are essential to maximize the profit from an underground mining project subject to inherent physical, geotechnical and geological constraints. Number of researches have been introduced for stope boundary optimization but true optimal solution in three dimensional spaces is still out of reach. This article proposed a computer programming based optimization model using mixed integer linear programming based algorithm that incorporate stope boundary optimization with varying cost of mining and selling price of the metal. An actual ore body model was taken as case study to implement the algorithm in real mining scenario. In validation study, it is observed that, by using proposed model, the profit can be increased by 10% - 15% as compared to the present stoping practice. Simulating the optimal stope boundary by changing the various cost and price parameters helps to opt the best possible option for a given mining scenario to make most realistic plan.

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42

Ali, Ziad M., Ibrahim Mohamed Diaaeldin, Shady H. E. Abdel Aleem, Ahmed El-Rafei, Almoataz Y. Abdelaziz, and Francisco Jurado. "Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty." Mathematics 9, no. 1 (2020): 26. http://dx.doi.org/10.3390/math9010026.

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Renewable energy integration has been recently promoted by many countries as a cleaner alternative to fossil fuels. In many research works, the optimal allocation of distributed generations (DGs) has been modeled mathematically as a DG injecting power without considering its intermittent nature. In this work, a novel probabilistic bilevel multi-objective nonlinear programming optimization problem is formulated to maximize the penetration of renewable distributed generations via distribution network reconfiguration while ensuring the thermal line and voltage limits. Moreover, solar, wind, and load uncertainties are considered in this paper to provide a more realistic mathematical programming model for the optimization problem under study. Case studies are conducted on the 16-, 59-, 69-, 83-, 415-, and 880-node distribution networks, where the 59- and 83-node distribution networks are real distribution networks in Cairo and Taiwan, respectively. The obtained results validate the effectiveness of the proposed optimization approach in maximizing the hosting capacity of DGs and power loss reduction by greater than 17% and 74%, respectively, for the studied distribution networks.

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Javadi Gargar, Farnaz i., and Mehdi Seifbarghy. "Solving multi-objective supplier selection and quota allocation problem under disruption using a scenario-based approach." Engineering review 40, no. 3 (2020): 78–89. http://dx.doi.org/10.30765/er.40.3.08.

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Nowadays, experts believe there are abundant sources of risks in a supply chain. An important group of risks against a supply chain is the disruption risks group, which disturbs the flow of material in the chain and may lead to inefficiency in providing the final product in the supply chain. The aim of this article is to investigate the control of costs of disruption in a supply chain by considering the possibility of disruption. In fact, this research focuses on determining the best combination of suppliers and quota allocation with regards to disruption in suppliers. The proposed multi-objective mathematical model in this paper is a mixed-integer programming (MIP) model with objective functions to minimize transaction costs of suppliers, expected costs of purchasing goods, expected percentages of delayed products, expected returned products, and to maximize expected evaluation scores of the selected suppliers. Due to the uncertainty of demand and supplier disruption in the real world, their values are also considered uncertain; the proposed multi-objective model is studied by using a scenario-based stochastic programming (SP) method. In this method, all possible predictions for demand and disruption values are simultaneously included in the model; objective function results have more optimal value than a separate solution of the model for each predicted value.

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44

Alexandron, Giora, Michal Armoni, Michal Gordon, and David Harel. "Teaching Scenario-Based Programming: An Additional Paradigm for the High School Computer Science Curriculum, Part 1." Computing in Science & Engineering 19, no. 5 (2017): 58–67. http://dx.doi.org/10.1109/mcse.2017.3421557.

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45

Alexandron, Giora, Michal Armoni, Michal Gordon, and David Harel. "Teaching Scenario-Based Programming: An Additional Paradigm for the High School Computer Science Curriculum, Part 2." Computing in Science & Engineering 19, no. 6 (2017): 64–71. http://dx.doi.org/10.1109/mcse.2017.3971162.

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46

Ferguson, Matthew D., Raymond Hill, and Brian Lunday. "A scenario-based parametric analysis of the army personnel-to-assignment matching problem." Journal of Defense Analytics and Logistics 4, no. 1 (2020): 89–106. http://dx.doi.org/10.1108/jdal-08-2019-0015.

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Purpose This study aims to compare linear programming and stable marriage approaches to the personnel assignment problem under conditions of uncertainty. Robust solutions should exhibit reduced variability of solutions in the presence of one or more additional constraints or problem perturbations added to some baseline problems. Design/methodology/approach Several variations of each approach are compared with respect to solution speed, solution quality as measured by officer-to-assignment preferences and solution robustness as measured by the number of assignment changes required after inducing a set of representative perturbations or constraints to an assignment instance. These side constraints represent the realistic assignment categorical priorities and limitations encountered by army assignment managers who solve this problem semiannually, and thus the synthetic instances considered herein emulate typical problem instances. Findings The results provide insight regarding the trade-offs between traditional optimization and heuristic-based solution approaches. Originality/value The results indicate the viability of using the stable marriage algorithm for talent management via the talent marketplace currently used by both the U.S. Army and U.S. Air Force for personnel assignments.

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Shao, Jian, Bu Han Zhang, Wei Si Deng, Kai Min Zhang, Bing Jie Jin, and Teng Yu Ge. "A Stochastic Programming Method for Unit Commitment of Wind Integrated Power System." Advanced Materials Research 732-733 (August 2013): 1390–95. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.1390.

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This paper presents a stochastic programming method that can assess the impact of wind generation uncertainties on unit comment (UC) problem. To model the uncertainty of wind genration, scenarios of wind speed are generated based on the known probability interval of forecasted wind speed and a scenario reduction technique limits the number of scenarios. The UC problem is modeled as a stochastic programming problem based on chance-constrained programming, and is decomposed into two embedded optimization sub-problems: the unit on/off status schedule problem and the load economic dispatch problem. Discrete particle swarm optimization (DPSO) and the equal incremental principle are used to solve the stochastic UC problem. The numerical results indicate that the proposed stochastic model is more suitable for wind integrated system with uncertainty.

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Bayram, Vedat, and Hande Yaman. "A stochastic programming approach for Shelter location and evacuation planning." RAIRO - Operations Research 52, no. 3 (2018): 779–805. http://dx.doi.org/10.1051/ro/2017046.

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Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.

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Tokola, Henri Alfred, Esko Niemi, and Heikki Remes. "Block Erection in the Event of Delays in Shipbuilding: A Scenario-Based Approach." Journal of Ship Production and Design 32, no. 01 (2016): 37–49. http://dx.doi.org/10.5957/jspd.2016.32.1.37.

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Ships are constructed from individual steel structural units called blocks, which are typically erected into the ship one by one in a sequence. This sequence, the block erection schedule, is the main schedule in shipbuilding, and it is followed in other production phases. However, the problems in the production of the blocks can delay the arrival of the blocks in comparison to what was initially scheduled. To deal with these delays, this article studies five different planning methods: erecting blocks unfinished; the use of inventories; the use of rush jobs; sequence changes; and, if the delays cannot be dealt with, delaying the completion of the ship. In order to do that, a mathematical, scenario-based mixed-integer linear programming model is formed. The model is used with numerical results to show that the block structure, delay conditions, and the tardiness costs have significant effect on the optimal use of planning methods. Results show that inventories should be used when delays are probable, whereas blocks should be erected unfinished if the delays are very uncertain and there are high tardiness penalties. The uses of rush jobs and sequence changes depend on the structure of the ship.

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Grudniak, Marcin, and Mariusz Dzieńkowski. "REST API performance comparison of web applications based on JavaScript programming frameworks." Journal of Computer Sciences Institute 19 (June 30, 2021): 121–25. http://dx.doi.org/10.35784/jcsi.2620.

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The aim of the work was to compare two technologies for creating server applications based on the JavaScript programming language. For the purposes of the research, two test applications were created. The first one was built on the basis of the Express programming framework and the second one on the basis of the Hapi framework. The client part of both applications was prepared using the React library. The client and server parts communicated with each other by means of REST API – the universal HTTP interface. The client application sent requests to the server application which then performed basic operations on the MongoDB basis and returned the result. As part of the work, an experiment consisting of four scenarios was developed. In each scenario, a different type of data was taken into consideration: a string of characters, an array, an object and an array of objects. The research focused on the efficiency aspect – measuring the response time of requests during GET, POST, PUT and DELETE operations. The tests were performed on two computers and the measurements were made in two ways: using a single code embedded in test applications and using the Postman tool. The obtained results, after averaging and analyzing them allowed for the conclusion that the Express framework proved to be more efficient than Hapi due to the shorter response time of requests. Only in the scenario where operations with large datasets were performed was the response time of requests at a similar level.

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