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This study investigates multi-store order delivery services where customers can order from multiple stores for home delivery. We first consider separated-ord...

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Ultra-fast delivery revolutionizes food and grocery services, with several companies advertising delivery times under 15 to 30 minutes. Motivated by the mult...

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For continuing tasks, average cost Markov decision processes have well- documented value and can be solved using efficient algorithms. However, it explici...

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We consider fair resource allocation in sequential decision-making environments modeled as weakly coupled Markov decision processes, where resource constrain...

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In mining complexes or mineral value chains, materials flow from extraction sites (mines) through crushers, stockpiles, waste dump and tailings, and processi...

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to account for tail risks associated with an uncertain loss. With limited data, the empirical entropic risk estimator, i.e. replacing the expectation in the ...

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Vehicle routing problems (VRPs) with deadlines have received significant attention around the world. Motivated by a real-world food delivery problem, we assu...

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Recently there has been a surge of interest in operations research~(OR) and the machine learning~(ML) community in combining prediction algorithms and optimi...

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Optimizing static risk-averse objectives in Markov decision processes is challenging because they do not readily admit dynamic programming decompositions. Pr...

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In order to improve the efficiency of the last-mile delivery system when customers are possibly absent for deliveries, we propose the idea of employing the c...

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In this paper, we study a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Specifically, we addres...

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This research focuses on the bid optimization problem in the real-time bidding setting for online display advertisements, where an advertiser, or the adverti...

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Recently equal risk pricing, a framework for fair derivative pricing, was extended to consider dynamic risk measures. However, all current implementations ei...

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We study a predisaster relief network design problem with uncertain demands. The aim is to determine the prepositioning and reallocation of relief supplies. ...

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The problem of portfolio management represents an important and challenging class of dynamic decision making problems, where rebalancing decisions need to be...

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Optimization with stochastic dominance constraints has recently received an increasing amount of attention in the quantitative risk management literature. In...

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Within the context of optimization under uncertainty, a well-known alternative to minimizing expected value or the worst-case scenario consists in minimizing...

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In this paper, we study a distributionally robust multi-item newsvendor problem, where the demand distribution is unknown but specified with a general event-...

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Battery charging of electric vehicles (EVs) needs to be properly coordinated by electricity producers to maintain the network reliability. In this paper, we ...

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