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Full-Text Articles in Engineering
Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj
Multi-Stage Stochastic Optimization And Reinforcement Learning For Forestry Epidemic And Covid-19 Control Planning, Sabah Bushaj
Dissertations
This dissertation focuses on developing new modeling and solution approaches based on multi-stage stochastic programming and reinforcement learning for tackling biological invasions in forests and human populations. Emerald Ash Borer (EAB) is the nemesis of ash trees. This research introduces a multi-stage stochastic mixed-integer programming model to assist forest agencies in managing emerald ash borer insects throughout the U.S. and maximize the public benets of preserving healthy ash trees. This work is then extended to present the first risk-averse multi-stage stochastic mixed-integer program in the invasive species management literature to account for extreme events. Significant computational achievements are obtained using …
Assessment Of Adaptability Of A Supply Chain Trading Agent’S Strategy: Evolutionary Game Theory Approach, Yoon Sang Lee, Riyaz T. Sikora
Assessment Of Adaptability Of A Supply Chain Trading Agent’S Strategy: Evolutionary Game Theory Approach, Yoon Sang Lee, Riyaz T. Sikora
Journal of International Technology and Information Management
With the increase in the complexity of supply chain management, the use of intelligent agents for automated trading has gained popularity (Collins, Arunachalam, B, et al. 2006). The performance of supply-chain agents depends on not just the market environment (supply and demand patterns) but also on what types of other agents they are competing with. For designers of such agents it is important to ascertain that their agents are robust and can adapt to changing market and competitive environments. However, to date there has not been any work done that assesses the adaptability of a trading agent’s strategy in the …