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Handling of long-term storage in multi-horizon stochastic programs
This paper introduces a method for incorporating long-term storage into the multi-horizon modelling paradigm, thereby expanding the scope of problems...
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Humanitarian Logistics Under Uncertainty: Planning for Sheltering and Evacuation
This chapter focuses on a major area emerging in the context of humanitarian logistics: emergency evacuation planning and management. Two major...
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Artificial Intelligence Computing and Nature-Inspired Optimization Techniques for Effective Supply Chain Management
The artificial intelligence (AI) and nature-inspired optimization (NIO) techniques can be used to reduce the impact of supply chain disruptions....
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Territory Design
This chapter discusses territory design problems under uncertainty. This is a topic much related to discrete p-median problems under uncertainty....
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Data-driven optimization for automated warehouse operations decarbonization
The rapid development of intelligent warehouse systems is resulting in the realization of automation in warehouse activities and raising awareness of...
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Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach
In today’s era, the importance and implementation of blockchain networks have become feasible as it improves the resilience of the supply chain...
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Statistical estimation of operating reserve requirements using rolling horizon stochastic optimization
We develop a multi-period stochastic optimization framework for identifying operating reserve requirements in power systems with significant...
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The PSO Family: Application to the Portfolio Optimization Problem
Nonlinear high-dimensional optimization problems are generally ill-posed and ill-conditioned, with different sets of models located in one or...
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A data-driven mathematical model to design a responsive-sustainable pharmaceutical supply chain network: a Benders decomposition approach
The pharmaceutical supply chain is unique to other supply chains due to certain characteristics. Medicine is classified as a valuable asset, and any...
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The Impact and Implications of Optimization
In this chapter many issues are touched upon which are part of more general operational research concerns, particularly when these are amplified by...
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Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach
Indian agricultural landscapes can provide solid empirical evidences on the immensity of farmer efficiency levels in comparable countries with a...
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A hybrid heuristic approach to master surgery scheduling with downstream resource constraints and dividable operating room blocks
This study considers a combination of strategic and tactical levels of operating room planning where two types of full-day and half-day blocks are...
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Simulation-Based Optimization
“Simulation refers to a broad collection of methods and applications to mimic the behavior of real systems, usually on a computer with appropriate...
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Distributions and bootstrap for data-based stochastic programming
In the context of optimization under uncertainty, we consider various combinations of distribution estimation and resampling (bootstrap and bagging)...
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Distributionally robust optimization with multiple time scales: valuation of a thermal power plant
The valuation of a real option is preferably done with the inclusion of uncertainties in the model, since the value depends on future costs and...
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Applications of Machine Learning in the Planning of Electric Vehicle Charging Stations and Charging Infrastructure: A Review
While electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) have the potential solution from an environmental perspective, they face an...
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Analysing supply chain coordination mechanisms dealing with repurposing challenges during Covid-19 pandemic in an emerging economy: a multi-layer decision making approach
Following the outbreak of the Covid-19 pandemic, there was a serious need for the pharmaceutical industry to combat the disease more quickly and...
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Hyperparameters Optimization of Deep Convolutional Neural Network for Detecting COVID-19 Using Differential Evolution
COVID-19 is one of the most dangerous diseases that appeared during the past 100 years, that caused millions of deaths worldwide. It caused hundreds...
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Can diverse and conflicting interests of multiple stakeholders be balanced?
Multiple stakeholders involved in the decision-making process have inherent interests that are sought to be maximized along with the collective goals...
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Hub Location
This chapter discusses models and solution techniques for hedging against uncertainty in hub location problems. This area grew significantly in a...