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نتیجه جستجو - Stochastic multi-objective optimization

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Simulation-based multi-objective model for supply chains with disruptions in transportation
شبیه سازی مبتنی بر مدل چند هدفه برای زنجیره تامین با اختلال در حمل و نقل-2017
Unpredictable disruptions (e.g., accidents, traffic conditions, among others) in supply chains (SCs) mo tivate the development of decision tools that allow designing resilient routing strategies. The transpor tation problem, for which a model is proposed in this paper, consists of minimizing the stochastic transportation time and the deterministic freight rate. This paper extends a stochastic multi-objective minimum cost flow (SMMCF) model by proposing a novel simulation-based multi-objective optimization (SimMOpt) solution procedure. A real case study, consisting of the road transportation of perishable agricultural products from Mexico to the United States, is presented and solved using the proposed SMMCF-Continuous/SimMOpt solution framework. In this case study, time variability is caused by the inspection of products at the U.S.-Mexico border ports of entry. The results demonstrate that this fra mework is effective and overcomes the limitations of the multi-objective stochastic minimum cost flow problem (which becomes intractable for large-scale instances).
Keywords: Minimum cost flow | Simulated annealing | Simulation optimization | Stochastic multi-objective optimization | Resilient supply chains
مقاله انگلیسی
2 Stochastic multi-objective optimization for economic-emission dispatch with uncertain wind power and distributed loads
بهینه سازی چند هدفه تصادفی برای توزیع انتشار-اقتصادی با نیروی باد نامشخص و بارهای توزیع شده-2014
This paper proposes a stochastic multi-objective optimization method for solving the Security Constrained Optimal Power Flow (SCOPF) problem with uncertain wind power and distributed load variations. The dispatch objectives are formulated to not only minimize the expectation of fuel costs and the deviation of the fuel cost distribution, but also to maximize wind power penetration while also considering variations in wind speed and distributed loads. The computational complexity of the stochastic optimization is a crucial issue that is considered when using a Paired-Bacteria Optimization (PBO) algorithm, which is simpler than most Evolutionary Algorithms (EAs). This paper reports the simu lation results obtained using an IEEE 30-bus system, including a comparison between the results achieved using the proposed method and those obtained from deterministic dispatch. The trade-off relationships between fuel cost, wind power penetration, and emissions are analyzed based on the Pareto set offeasible solutions resulted from PBO. This analysis allows for the determination of the optimal dispatch actions that simultaneously minimize all of the objectives while considering uncertainties in wind power and distributed loads. Keywords: Stochastic dispatch Wind power Paired-bacteria optimizer Distributed loads Emission Multi-objective optimization
مقاله انگلیسی
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