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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 |