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Cost of fairness in agent scheduling for contact centers
(American Institute of Mathematical Sciences, 2022-03)
We study a workforce scheduling problem faced in contact centers with considerations on a fair distribution of shifts in compliance with agentpreferences. We develop a mathematical model that aims to minimize operatingcosts ...
Robust parameter design and optimization for quality engineering
(Springer, 2022-03)
This paper proposes a methodology to determine the optimal settings of key decision variables that affect the resilience of an engineering design against uncertainty. Uncertainty in quality engineering is often caused by ...
A fluid approximation for the single-leg fare allocation problem with nonhomogeneous poisson demand
(Springer, 2022-02-27)
Fare allocation for legs and O&D pairs plays a crucial role in airline revenue management. Despite a large number of dynamic pricing studies, there are only a few widely adopted studies in which assumptions affect most ...
A capacitated mobile facility location problem with mobile demand: Recurrent service provision to en route refugees
(OpenProceedings.org, 2022)
In this paper, we help humanitarian organizations provide service via mobile facilities (MFs) to migrating refugees, who attempt to cross international borders. Over a planning horizon, we aim to optimize number and routes ...
Capacitated stochastic lot-sizing and production planning problem under demand uncertainty
(Elsevier, 2022)
This paper proposes two multi-period, multi-item capacitated stochastic lot-sizing problems under demand uncertainty. We model uncertainty via a scenario tree. The first model considers production, inventory, backlogging, ...
Stochastic production planning with flexible manufacturing systems and uncertain demand: A column generation-based approach
(Elsevier, 2022)
The ongoing pandemic, namely COVID-19, has rendered widespread economic disorder. The deficiencies have delayed production at manufacturers in several industries on the supply side. The effects of disruption were more ...
Deep reinforcement learning approach for trading automation in the stock market
(IEEE, 2022)
Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining the financial assets price 'prediction' ...
A mathematical model for equitable in-country COVID-19 vaccine allocation
(Taylor and Francis, 2022)
Given the scarcity of COVID-19 vaccines, equitable (fair) allocation of limited vaccines across the main administrative units of a country (e.g. municipalities) has been an important concern for public health authorities ...
Summary of an effective formulation of the multi-criteria test suite minimization problem
(IEEE, 2022)
This is an extended abstract of the article: Okan Orsan Ozener and Hasan Sozer, 'An Effective Formulation of the Multi-Criteria Test Suite Minimization Problem', published in the Journal of Systems and Software, Vol. 168, ...
Variable-sized bin packing problem with conflicts and item fragmentation
(Elsevier, 2022-01)
In this paper, we study the Variable-Sized Bin Packing Problem with Conflicts and Item Fragmentation (VSBPPC-IF) that has applications such as (i) the delivery planning of incompatible items using a fleet of heterogenous ...
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