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Journal articles on the topic 'Optimization scenario'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

Dembo, Ron S. "Scenario optimization." Annals of Operations Research 30, no. 1 (1991): 63–80. http://dx.doi.org/10.1007/bf02204809.

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Ryan, Kevin, Shabbir Ahmed, Santanu S. Dey, Deepak Rajan, Amelia Musselman, and Jean-Paul Watson. "Optimization-Driven Scenario Grouping." INFORMS Journal on Computing 32, no. 3 (2020): 805–21. http://dx.doi.org/10.1287/ijoc.2019.0924.

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Scenario decomposition algorithms for stochastic programs compute bounds by dualizing all nonanticipativity constraints and solving individual scenario problems independently. We develop an approach that improves on these bounds by reinforcing a carefully chosen subset of nonanticipativity constraints, effectively placing scenarios into groups. Specifically, we formulate an optimization problem for grouping scenarios that aims to improve the bound by optimizing a proxy metric based on information obtained from evaluating a subset of candidate feasible solutions. We show that the proposed group

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Vonk, E., Y. P. Xu, M. J. Booij, and D. C. M. Augustijn. "Quantifying the robustness of optimal reservoir operation for the Xinanjiang-Fuchunjiang Reservoir Cascade." Water Supply 16, no. 1 (2015): 79–86. http://dx.doi.org/10.2166/ws.2015.116.

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In this research we investigate the robustness of the common implicit stochastic optimization (ISO) method for dam reoperation. As a case study, we focus on the Xinanjiang-Fuchunjiang reservoir cascade in eastern China, for which adapted operating rules were proposed as a means to reduce the impact of climate change and socio-economic developments. The optimizations were based on five different water supply and demand scenarios for the future period from 2011 to 2040. Main uncertainties in the optimization can be traced back to correctness of the assumed supply and demand scenarios and the qua

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Qian, Xinbo, Qiuhua Tang, and Bo Tao. "A Novel Scenario Reduction Method by 3D-Outputs Clustering for Condition-Based Maintenance Optimization." International Journal of Reliability, Quality and Safety Engineering 24, no. 04 (2017): 1750018. http://dx.doi.org/10.1142/s0218539317500188.

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Condition-based maintenance (CBM) optimization involves considering inherent uncertainties and external uncertainties. Since computational complexity increases exponentially with the number of degradation uncertainties and stages, scenario reduction aims to select small set of typical scenarios which can maintain the probability distributions of outputs of possible scenarios. A novel scenario reduction method, 3D-outputs-clustering scenario reduction (3DOCS), is presented by considering the impacts of uncertainty parameters on the output performance for CBM optimization which have been overloo

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Wang, Yishen, Yuzong Liu, and Daniel S. Kirschen. "Scenario Reduction With Submodular Optimization." IEEE Transactions on Power Systems 32, no. 3 (2017): 2479–80. http://dx.doi.org/10.1109/tpwrs.2016.2603448.

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Campi, M. C., and S. Garatti. "Wait-and-judge scenario optimization." Mathematical Programming 167, no. 1 (2016): 155–89. http://dx.doi.org/10.1007/s10107-016-1056-9.

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Luo, Li Zhe, Xue Hong Yang, Wen Zhen Yu, and Shao Hua Pan. "Diversion System Scenarios Optimization Considering Indicators Correlation." Advanced Materials Research 1065-1069 (December 2014): 2554–60. http://dx.doi.org/10.4028/www.scientific.net/amr.1065-1069.2554.

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The decision-making indicators of hydropower engineering diversion scenario are always related with diversion risk, and for determining the optimal scenario, correlation analysis and decoupling for indicators is the key problem. Using k-additive fuzzy measure to characterize and decouple the relevance of indicators on the base of the analysis and quantization of indicators, and determining the weights of indicators according to maximum fuzzy measure entropy principle, finally the synthetic appraisal value for diversion scenarios can be calculated with choquet integral to rank and select optima

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Kwon, Soon Ho, Donghwi Jung, and Joong Hoon Kim. "Development of a Multiscenario Planning Approach for Urban Drainage Systems." Applied Sciences 10, no. 5 (2020): 1834. http://dx.doi.org/10.3390/app10051834.

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A traditional urban drainage system (UDS) planning approach generally considers the most probable future rainfall scenario. However, this single scenario (i.e., scenario-optimal) planning approach is prone to failure under recent climatic conditions, which involve increasing levels of uncertainty. To overcome this limitation, an alternative is to consider multiple scenarios simultaneously. A two-phase multi-scenario-based UDS planning approach was developed. Scenario-optimal solutions were determined for a set of scenarios in Phase I, as the traditional planning approach, while common elements

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Sales, Agust, Duberlí Geomar Elera Gonzáles, Thales Guilherme Vaz Martins, et al. "Optimization of Skid Trails and Log Yards on the Amazon Forest." Forests 10, no. 3 (2019): 252. http://dx.doi.org/10.3390/f10030252.

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Research highlights: We used Dijkstra Algorithm (DA) to define optimal allocation of yards in order to minimize total skid-trail’s distance in the Amazon Forest. DA minimized trails’ distances and associated transportation costs, leading to an even smaller value when the current planning was disregarded and suggesting the reduction of deleterious environmental externalities. Background and objectives: We sought to answer if it is possible to optimize distances and intrinsic costs in the management of Amazonian forests using DA. The objective was to minimize skid trails distances by best alloca

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Jiang, Honglei, Xia Xu, Lingfei Wang, and Tong Zhang. "Integrating Ecosystem Service Values and Economic Benefits for Sustainable Land Use Management in Semi-Arid Regions in Northern China." Sustainability 13, no. 18 (2021): 10431. http://dx.doi.org/10.3390/su131810431.

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Studies on land use structural optimization can support the sustainability of land resources. The Taipusi Banner lies in the arid and semiarid area of northern China, with rapid economic development and a vulnerable ecological condition. Taking the Taipusi Banner as a research case, we adopted a land use map and statistical data, and employed the ecosystem process model to establish five scenarios, including an economically optimal scenario, an ecologically optimal scenario, a comprehensively optimal scenario, a status quo, and a projected scenario. Based on multi-objective linear programming,

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An, Hyunjin, and Sangmin Lee. "A Utility Maximized Harvest Decision Model for Privately Owned Coniferous Forests in the Republic of Korea." Forests 11, no. 12 (2020): 1273. http://dx.doi.org/10.3390/f11121273.

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This study examined optimal harvesting decisions of multiple age-class private forests that maximize private forest owners’ utility. For this analysis, we developed two scenarios. One scenario was to maintain the harvest level currently performed in the Republic of Korea (ROK) (baseline scenario), and the other was to harvest according to the harvest prescription derived from the discrete-time utility model with a multiple age-class forest (optimization scenario). For the baseline scenario, the cohort component approach was applied to predict changes in the forest’s age structure under the giv

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Kitta, Ikhlas. "Perbaikan Level Tegangan dan Reduksi Rugi-Rugi Sistem Transmisi Sulbagsel Berbasis Ant Colony Optimization." INTEK: Jurnal Penelitian 6, no. 1 (2019): 1. http://dx.doi.org/10.31963/intek.v6i1.1121.

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Abstract—The Ant Colony Optimization (ACO) method is used to determine the location and optimal amount of bank capacitors in the South Sulawesi electric power system (Sulbagsel). The purpose of employing ACO is to determine the ability of ACO as one method for optimization to improve voltage levels and reduce power losses in the electric power system. There are 5 scenarios carried out in this study, scenario 4 and scenario 5 are scenarios for applying the ACO method, the results of these two scenarios are the increase in voltage on the bus and the reduction of power losses in the Sulbagsel sys

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Lam, Henry, and Fengpei Li. "Parametric Scenario Optimization under Limited Data." ACM Transactions on Modeling and Computer Simulation 30, no. 4 (2020): 1–41. http://dx.doi.org/10.1145/3410152.

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Kumar, Manoj. "Scenario and Robust Optimization in Risk Management." International Journal of Risk and Contingency Management 5, no. 4 (2016): 27–41. http://dx.doi.org/10.4018/ijrcm.2016100103.

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Simulation Optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of Simulation Optimization for managing risk. Recent advances in Simulation Optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk and uncertainty, Simulation Optimization surpasses the capabilities of other optimization methods, not only in the quality of solutions, but also in their interpretability and practicality. In this paper,

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Rostampour, Vahab, and Tamás Keviczky. "Distributed Computational Framework for Large-Scale Stochastic Convex Optimization." Energies 14, no. 1 (2020): 23. http://dx.doi.org/10.3390/en14010023.

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This paper presents a distributed computational framework for stochastic convex optimization problems using the so-called scenario approach. Such a problem arises, for example, in a large-scale network of interconnected linear systems with local and common uncertainties. Due to the large number of required scenarios to approximate the stochasticity of these problems, the stochastic optimization involves formulating a large-scale scenario program, which is in general computationally demanding. We present two novel ideas in this paper to address this issue. We first develop a technique to decomp

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Isharyati, Ade Widya, Agus Prasetya, and Rochim Bakti Cahyono. "Optimization of operational techniques in waste management case study: Lhokseumawe City." E3S Web of Conferences 76 (2019): 03007. http://dx.doi.org/10.1051/e3sconf/20197603007.

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The high volume of waste that is not followed by properly waste management method, makes the waste management in Lhokseumawe not optimal. This problem is shown by the level of waste service is only about 38 %, while the waste that is not transported will be cumulative in any places. This is showed that the level of waste service is below of the minimum service standard that is 60 %–90 %. It is necessary to improve the waste management, especially in the utilization of waste to reduce the waste and landfill load. This research aims to evaluated and analysis of waste management in Lhokseumawe by

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Mustafa, Mohammed Obaid. "Optimal parameter values of PID controller for DC motor based on modified particle swarm optimization with adaptive inertia weight." Eastern-European Journal of Enterprise Technologies 1, no. 2 (109) (2021): 35–45. http://dx.doi.org/10.15587/1729-4061.2021.225383.

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A significant problem in the control field is the adjustment of PID controller parameters. Because of its high nonlinearity property, control of the DC motor system is difficult and mathematically repetitive. The particle swarm optimization PSO solution is a great optimization technique and a promising approach to address the problem of optimum PID controller results. In this paper, a modified particle swarm optimization PSO method with four inertia weight functions is suggested to find the global optimum parameters of the PID controller for speed and position control of the DC motor. Benchmar

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18

Ren, Feng, and Long Xia. "Analysis of China’s Primary Energy Structure and Emissions Reduction Targets by 2030 Based on Multiobjective Programming." Mathematical Problems in Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/1532539.

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China’s energy issues and carbon emissions have become important global concerns. The purpose of this paper is to analyze the fulfillment of China’s commitment to carbon emissions reduction by 2030. We establish the Markov chain model to analyze the transition of primary energy structure and carbon emissions in China by 2030 without artificial intervention and build three multiobjective optimization models to analyze China’s energy structure and emissions reduction targets by 2030 under three scenarios (scenario of energy structure optimization, scenario of energy intensity optimization, and s

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Sankary, Nathan, and Avi Ostfeld. "Stochastic Scenario Evaluation in Evolutionary Algorithms Used for Robust Scenario-Based Optimization." Water Resources Research 54, no. 4 (2018): 2813–33. http://dx.doi.org/10.1002/2017wr022068.

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Wang, Bing, Xiao Yan Li, and He Xia Meng. "Two-Level Robust Optimization for Uncertain Job Shop Scheduling Problem." Advanced Materials Research 1039 (October 2014): 514–21. http://dx.doi.org/10.4028/www.scientific.net/amr.1039.514.

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This paper proposes a two-level robust optimization model in the context of job shop scheduling problem. The job shop scheduling problem optimizes the makespan under uncertain processing times, which are described by a set of scenarios. In the first-level optimization, a traditional stochastic optimization model is conducted to obtain the optimal expected performance as a standard performance, on which a concept of bad-scenario set is defined. In the second-level optimization, a robustness measure is given based on bad-scenario set. The objective function for the second robust optimization mod

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21

Sanchis-Cano, Angel, Luis Guijarro, and Massimo Condoluci. "Dynamic capacity provision for wireless sensors’ connectivity: A profit optimization approach." International Journal of Distributed Sensor Networks 14, no. 4 (2018): 155014771877254. http://dx.doi.org/10.1177/1550147718772544.

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We model a wireless sensors’ connectivity scenario mathematically and analyze it using capacity provision mechanisms, with the objective of maximizing the profits of a network operator. The scenario has several sensors’ clusters with each one having one sink node, which uploads the sensing data gathered in the cluster through the wireless connectivity of a network operator. The scenario is analyzed both as a static game and as a dynamic game, each one with two stages, using game theory. The sinks’ behavior is characterized with a utility function related to the mean service time and the price

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Paskalathis, Victor, and Azhari SN. "Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 11, no. 2 (2017): 109. http://dx.doi.org/10.22146/ijccs.16631.

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Common practice in crowdsourced delivery services is through direct delivery. That is by dispatching direct trip to a driver nearby the origin location. The total distance can be reduced through multiple pickup and delivery by increasing the number of requests in a trip.The research implements exact algorithm to solve the consolidation problem with up to 3 requests in a trip. Greedy heuristic is performed to construct initial route based on highest savings. The result is then optimized using Ant Colony Optimization (ACO). Four scenarios are compared. A direct delivery scenarios and three multi

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23

Mausser, Helmut, and Dan Rosen. "Applying Scenario Optimization to Portfolio Credit Risk." Journal of Risk Finance 2, no. 2 (2001): 36–48. http://dx.doi.org/10.1108/eb043460.

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VILLÁNYI, Balázs, and Péter MARTINEK. "Automation of Scenario-Based Schema Matcher Optimization." Acta Electrotechnica et Informatica 16, no. 1 (2016): 3–10. http://dx.doi.org/10.15546/aeei-2016-0001.

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25

Calafiore, Giuseppe C., and Lorenzo Fagiano. "Robust Model Predictive Control via Scenario Optimization." IEEE Transactions on Automatic Control 58, no. 1 (2013): 219–24. http://dx.doi.org/10.1109/tac.2012.2203054.

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Romanko, Oleksandr, and Helmut Mausser. "Robust scenario-based value-at-risk optimization." Annals of Operations Research 237, no. 1-2 (2015): 203–18. http://dx.doi.org/10.1007/s10479-015-1822-8.

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27

Wehner, W. P., E. Schuster, M. D. Boyer, and F. M. Poli. "TRANSP-based optimization towards tokamak scenario development." Fusion Engineering and Design 146 (September 2019): 547–50. http://dx.doi.org/10.1016/j.fusengdes.2019.01.019.

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28

Wang, Ying, Peipei Shang, Lichun He, Yingchun Zhang, and Dandan Liu. "Can China Achieve the 2020 and 2030 Carbon Intensity Targets through Energy Structure Adjustment?" Energies 11, no. 10 (2018): 2721. http://dx.doi.org/10.3390/en11102721.

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To mitigate global warming, the Chinese government has successively set carbon intensity targets for 2020 and 2030. Energy restructuring is critical for achieving these targets. In this paper, a combined forecasting model is utilized to predict primary energy consumption in China. Subsequently, the Markov model and non-linear programming model are used to forecast China’s energy structure in 2020 and 2030 in three scenarios. Carbon intensities were forecasted by combining primary energy consumption, energy structure and economic forecasting. Finally, this paper analyzes the contribution potent

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Antoniou, Margarita, and Gregor Papa. "Differential Evolution with Estimation of Distribution for Worst-Case Scenario Optimization." Mathematics 9, no. 17 (2021): 2137. http://dx.doi.org/10.3390/math9172137.

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Worst-case scenario optimization deals with the minimization of the maximum output in all scenarios of a problem, and it is usually formulated as a min-max problem. Employing nested evolutionary algorithms to solve the problem requires numerous function evaluations. This work proposes a differential evolution with an estimation of distribution algorithm. The algorithm has a nested form, where a differential evolution is applied for both the design and scenario space optimization. To reduce the computational cost, we estimate the distribution of the best worst solution for the best solutions fo

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IQBAL, M. A., J. EITZINGER, H. FORMAYER, A. HASSAN, and L. K. HENG. "A simulation study for assessing yield optimization and potential for water reduction for summer-sown maize under different climate change scenarios." Journal of Agricultural Science 149, no. 2 (2011): 129–43. http://dx.doi.org/10.1017/s0021859610001243.

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SUMMARYThe objective of the present paper was to study the impact of climate change on grain yield, water balance, crop water productivity (CWP) and water requirements for the summer-sown maize in Faisalabad, Pakistan. Climate-change scenarios (Special Report on Emission Scenarios (SRES) A1B, A2 and B1) were derived from the general circulation model ECHAM 5 and the crop model CERES-Maize was used to simulate impacts of the applied climate scenarios. Calibration and validation of the crop models were carried out for the summer-sown maize in 2007 and for the spring-sown maize in 2008. Three pre

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Méndez, Maikel, José A. Araya, and Luís D. Sánchez. "Automated parameter optimization of a water distribution system." Journal of Hydroinformatics 15, no. 1 (2012): 71–85. http://dx.doi.org/10.2166/hydro.2012.028.

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The hydraulic model EPANET was applied and calibrated for the water distribution system (WDS) of La Sirena, Colombia. The Parameter ESTimator (PEST) was used for parameter optimization and sensitivity analysis. Observation data included levels at water storage tanks and pressures at monitoring nodes. Adjustable parameters were grouped into different classes according to two different scenarios identified as constrained and unconstrained. These scenarios were established to evaluate the effect of parameter space size and compensating errors over the calibration process. Results from the unconst

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Xie, Wu, Wenzhe Guo, Wenbin Shao, Fangyi Li, and Zhipeng Tang. "Environmental and Health Co-Benefits of Coal Regulation under the Carbon Neutral Target: A Case Study in Anhui Province, China." Sustainability 13, no. 11 (2021): 6498. http://dx.doi.org/10.3390/su13116498.

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Coal regulation has been implemented throughout China. However, the potential benefits of pollution abatement and the co-benefits of residents’ health were rarely assessed. In this study, based on the analysis of historical coal consumption and multiple coal regulation measures in Anhui Province, China, four scenarios (Business as Usual (BU), Structure Optimization (SO), Gross Consumption Control (GC), and Comprehensive Measures (CM)) were constructed to indicate four different paths from 2020 to 2060, which is a vital period for realizing carbon neutrality. The results show that reductions of

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Hassanjabbar, Amin, Bahram Saghafian, and Saeed Jamali. "Multi-reservoir system management under alternative policies and environmental operating conditions." Hydrology Research 49, no. 6 (2018): 1817–30. http://dx.doi.org/10.2166/nh.2018.150.

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Abstract In this paper, alternative reservoir operation models under different environmental operating conditions were developed to analyze the impacts of applying different policies in a multi-reservoir system in order to balance human and environmental requirements. Three scenarios/models were developed under four sub-scenarios/operating conditions. The scenarios were: (1) an optimization model to maximize the hydropower production, (2) an optimization model to minimize the squared of the difference between the release and need, (3) a simulation model under the Hydropower Standard Operating

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Günther, Matthias, and Michael Eichinger. "Cost optimization for the 100% renewable electricity scenario for the Java-Bali grid." International Journal of Renewable Energy Development 7, no. 3 (2018): 269–76. http://dx.doi.org/10.14710/ijred.7.3.269-276.

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A 100% renewable electricity supply is no insurmountable technical problem anymore after the respective technologies to harvest the energy from multiple renewable energy sources have been developed and have reached a high level of maturity. A problem may rather be suspected to reside on the economic side of an exclusively renewable electricity supply. The present study examines the economic implications of a renewable energy scenario for the Java-Bali grid. Based on given energy supply scenarios, the costs of an electricity supply from renewable energy sources alone are determined. Economic op

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Rocchetta, Roberto, Luis G. Crespo, and Sean P. Kenny. "A scenario optimization approach to reliability-based design." Reliability Engineering & System Safety 196 (April 2020): 106755. http://dx.doi.org/10.1016/j.ress.2019.106755.

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Gülpınar, Nalan, Berç Rustem, and Reuben Settergren. "Simulation and optimization approaches to scenario tree generation." Journal of Economic Dynamics and Control 28, no. 7 (2004): 1291–315. http://dx.doi.org/10.1016/s0165-1889(03)00113-1.

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Kim, Boeun, Jakob K. Huusom, and Jay H. Lee. "Robust Batch-to-Batch Optimization with Scenario Adaptation." Industrial & Engineering Chemistry Research 58, no. 30 (2019): 13664–74. http://dx.doi.org/10.1021/acs.iecr.8b06233.

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Abel, O., and W. Marquardt. "Scenario-integrated modeling and optimization of dynamic systems." AIChE Journal 46, no. 4 (2000): 803–23. http://dx.doi.org/10.1002/aic.690460414.

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Glanzer, Martin, and Georg Ch Pflug. "Multiscale stochastic optimization: modeling aspects and scenario generation." Computational Optimization and Applications 75, no. 1 (2019): 1–34. http://dx.doi.org/10.1007/s10589-019-00135-4.

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Abstract Real-world multistage stochastic optimization problems are often characterized by the fact that the decision maker may take actions only at specific points in time, even if relevant data can be observed much more frequently. In such a case there are not only multiple decision stages present but also several observation periods between consecutive decisions, where profits/costs occur contingent on the stochastic evolution of some uncertainty factors. We refer to such multistage decision problems with encapsulated multiperiod random costs, as multiscale stochastic optimization problems.

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Giuseppe, Ramogida, Cocilovo Valter, Coletti Alberto, et al. "Optimization of the IGNITOR operating scenario at 11MA." Fusion Engineering and Design 74, no. 1-4 (2005): 507–14. http://dx.doi.org/10.1016/j.fusengdes.2005.06.211.

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Kaut, Michal. "Scenario generation by selection from historical data." Computational Management Science 18, no. 3 (2021): 411–29. http://dx.doi.org/10.1007/s10287-021-00399-4.

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AbstractIn this paper, we present and compare several methods for generating scenarios for stochastic-programming models by direct selection from historical data. The methods range from standard sampling and k-means, through iterative sampling-based selection methods, to a new moment-based optimization approach. We compare the models on a simple portfolio-optimization model and show how to use them in a situation when we are selecting whole sequences from the data, instead of single data points.

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She, Chung, and Han. "Economic and Environmental Optimization of the Forest Supply Chain for Timber and Bioenergy Production from Beetle-Killed Forests in Northern Colorado." Forests 10, no. 8 (2019): 689. http://dx.doi.org/10.3390/f10080689.

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Harvesting mountain pine beetle-infested forest stands in the northern Colorado Rocky Mountains provides an opportunity to utilize otherwise wasted resources, generate net revenues, and minimize greenhouse gas (GHG) emissions. Timber and bioenergy production are commonly managed separately, and their integration is seldom considered. Yet, degraded wood and logging residues can provide a feedstock for bioenergy, while the sound wood from beetle-killed stands can still be used for traditional timber products. In addition, beneficial greenhouse gas emission (GHG) savings are often realized only b

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Büsing, Christina, Arie M. C. A. Koster, and Manuel Kutschka. "Recoverable robust knapsacks: the discrete scenario case." Optimization Letters 5, no. 3 (2011): 379–92. http://dx.doi.org/10.1007/s11590-011-0307-1.

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He, Bing Yan, Zhi Ming Zhu, and Tian Miao Shen. "The Scenario Analysis of Low-Carbon Development on the Basis of Improved IPAT Model in China." Advanced Materials Research 1010-1012 (August 2014): 2050–54. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.2050.

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It is an important strategic choice for countries to develop low-carbon economy while dealing with climate change. The paper gives a forecast and analysis on population, economic development, technology, energy consumption and CO2 emissions variation in China before 2020 as setting the year 2007 as the base year by using IPAT model. Three scenarios of CO2 emissions are set including business as usual (BAU), energy efficiency improvement scenario (EEI), and low carbon scenario (LC). The result shows that the LC scenario is the most appropriate and the most feasible scenario for China to achieve

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Choi, Yun, Kim, Jin, and Kim. "Robust Optimization Approach Using Scenario Concepts for Artillery Firing Scheduling Under Uncertainty." Applied Sciences 9, no. 14 (2019): 2811. http://dx.doi.org/10.3390/app9142811.

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Real wars involve a considerable number of uncertainties when determining firing scheduling. This study proposes a robust optimization model that considers uncertainties in wars. In this model, parameters that are affected by enemy’s behavior and will, i.e., threats from enemy targets and threat time from enemy targets, are assumed as uncertain parameters. The robust optimization model considering these parameters is an intractable model with semi-infinite constraints. Thus, this study proposes an approach to obtain a solution by reformulating this model into a tractable problem; the approach

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Abdallah, Mohamed, Mohamad Adghim, Munjed Maraqa, and Elkhalifa Aldahab. "Simulation and optimization of dynamic waste collection routes." Waste Management & Research 37, no. 8 (2019): 793–802. http://dx.doi.org/10.1177/0734242x19833152.

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Smart waste collection strategies have been developed to replace conventional fixed routes with dynamic systems that respond to the actual fill-level of waste bins. The variation in waste generation patterns, which is the main driver for the profit of smart systems, is exacerbated in the United Arab Emirates (UAE) due to a high expatriate ratio. This leads to significant changes in waste generation during breaks and seasonal occasions. The present study aimed to evaluate a geographic information system (GIS)-based smart collection system (SCS) compared to conventional practices in terms of tim

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De Sousa Santos, Natália Cibele, Daniel Ribeiro Gomes, Jarbas Ancelmo Da Silva Júnior, Stella Jacyszyn Bachega, and Dalton Matsuo Tavares. "Simulation-based optimization of the polca ordering system." Independent Journal of Management & Production 12, no. 2 (2021): 672–90. http://dx.doi.org/10.14807/ijmp.v12i2.1275.

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Given an increase in consumer demand for product quality, companies need to continually improve their means of production. The use of computational resources assists companies to choose an ordering system that best suits their reality. In this sense, the present study aims to analyze and compare the performance of the Paired-cell Overlapping Loops of Cards with Authorization (POLCA) system, according to pre-established parameters in a real automobile company case, which has a flow-shop production environment. In order to do this, the research has a hypothetical-deductive scientific explanation

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Ghanbari, Milad, Armin Monir Abbasi, and Mehdi Ravanshadnia. "Economic and Environmental Evaluation and Optimal Ratio of Natural and Recycled Aggregate Production." Advances in Materials Science and Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/7458285.

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Steady increase in overexploitation of stone quarries, generation of construction and demolition waste, and costs of preparing extra landfill space have become environmental and waste management challenges in metropolises. In this paper, aggregate production is studied in two scenarios: scenario 1 representing the production of natural aggregates (NA) and scenario 2 representing the production of recycled aggregates (RA). This study consists of two parts. In the first part, the objective is the environmental assessment (energy consumption and CO2 emission) and economic (cost) evaluation of the

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49

Miao, Hongchang, Donglin Li, Qiting Zuo, Lei Yu, Xiaoxia Fei, and Lingang Hao. "A Scenario-Based Optimization Model for Planning Sustainable Water-Resources Process Management under Uncertainty." Processes 7, no. 5 (2019): 312. http://dx.doi.org/10.3390/pr7050312.

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Discrepancies between water demand and supply are intensifying and creating a need for sustainable water resource process management associated with rapid economic development, population growth, and urban expansion. In this study, a scenario-based interval fuzzy-credibility constrained programming (SIFCP) method is developed for planning a water resource management system (WRMS) that can handle uncertain information by using interval values, fuzzy sets, and scenario analysis. The SIFCP-WRMS model is then applied to plan the middle route of the South-to-North Water Diversion Project (SNWDP) in

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Li, Zeng, Jingying Fu, Gang Lin, Dong Jiang, Kun Liu, and Yaxin Wang. "Multi-Scenario Analysis of Energy Consumption and Carbon Emissions: The Case of Hebei Province in China." Energies 12, no. 4 (2019): 624. http://dx.doi.org/10.3390/en12040624.

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In view of the complexity of the energy system and its complex relationship with socio-economic factors, this study adopts the Long-range Energy Alternative Planning (LEAP) model, a technology-based, bottom-up approach, scenario-based analysis, to develop a systematic analysis of the current and future energy consumption, supply and associated Green House Gas (GHG) emissions from 2015 to 2050. The impact of various energy policies on the energy system in Hebei Province was analysed by considering four scenarios: a Reference Scenario (REF), Industrial Structure Optimization Scenario (ISO), Term

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