Electrical Vehicle Charging Coordination Algorithms Framework

Nguyen, Nhan-Quy; Yalaoui, Farouk; Chehade, Hicham; Toggenburger, Pascal

doi:10.1007/978-3-319-75690-5_16

Cited by 4 publications

(4 citation statements)

References 35 publications

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“…By assuming that the input is only patients with a single session and that consultation and installation time are zero, the considered problem without resources constraints is reduced to the two stages Flow Shop problem, which is NP-hard [10]. Furthermore, the resource variation is usually seen as an element that makes the planning/scheduling problem harder to solve [11]. Our problem thus should be at least NP-hard.…”

Section: Problem Complexitymentioning

confidence: 99%

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Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service

et al. 2022

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In this paper, we study a complex outpatient planning problem in the chemotherapy department. The planning concerns sequences of patients’ treatment sessions subject to exact in-between resting periods (i.e., exact time-lags). The planning is constrained by the hospital infrastructure and the availability of medical staff (i.e., multiple time-varying resources’ availability). In order to maximize the patients’ service quality, the objective of the function considered is to minimize the total wait times, which is equivalent to the criteria for minimizing the total completion time. Our main contribution is a thorough analysis of this problem, using the Hybrid Flow Shop problem as a theoretical framework to study the problem. A novel Mixed Integer Linear Programming (MILP) is introduced. Concerning the resolution methods, priority-based heuristics and an adapted genetic algorithm (GA) are presented. Numerical experiments are conducted on historical data to compare the performances of the approximate resolution methods against the MILP solved by CPLEX. Numerical results confirm the performances of the proposed methods.

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Section: Problem Complexitymentioning

confidence: 99%

“…Operations: (11) obligates any operation to start and end exactly once on the horizon, according to (3). ( 12) makes each operation non-preemptive, which means that, once an operation starts, it must be processed without interruption.…”

Section: Mathematical Modelmentioning

confidence: 99%

Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service

et al. 2022

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“…By assuming that the input is only patients with a single session and that consultation and installation time are zero, the considered problem without resource constraints is reduced to the two stages as given in the flow shop problem, which is NP-hard [45]. Furthermore, resource variation is usually seen as an element that makes the planning/scheduling problem harder to solve [46]. Our problem should thus be at least NP-hard.…”

Section: Literature Reviewmentioning

confidence: 99%

Robust Appointment Scheduling in Healthcare

et al. 2022

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The quality and experience of healthcare systems affect the economy and prosperity of cities all over the world. Governments of several countries are struggling to improve the efficiency of their healthcare systems and decrease healthcare spending costs. In this paper, we discuss one of the most critical and busy processes among healthcare topics: ambulatory care center (ACC) appointment scheduling systems. We investigate the appointment-scheduling issue using a robust optimization framework to minimize operational costs while ensuring the improvement of healthcare service quality. Our findings and insights provide healthcare practitioners with tools to improve operational efficiency and service quality.

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“…gence creates the opportunity to analyze the data without a team analyst and the data can be used in prediction and reaction conditions. All these steps, shown in Figure 18, provide real-time decision-making approaches that make our planning faster, more precise, and more efficient [41].…”

Section: Digital Decision-makingmentioning

confidence: 99%

Industry 4.0: Revolution or Evolution?

Asadollahi-Yazdi¹,

Couzon²,

Nguyen³

et al. 2020

AJOR

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"Industry 4.0" term is devoted to the fourth industrial revolution. Over time and by developing different technologies, this term is coming with the new paradigm and technologies, which help to connect the machines, products, and methods as an interconnected system. This paper aims to introduce an analysis and a reflection around the concepts industry 4.0 and their impacts in the actual industrial world. The effects of this digitalization will be investigated on supply chain systems, decision-making processes, and business models. The classic supply chain is evolving into a Network Supply System (NSS) that is an interconnected supply chain with more focus on product and customer expectations. The global value chain process tends to be product-oriented. Smart data make the decisions more dynamic, flexible, and precise. Therefore, every industrial sector has to be adapted to this digital transformation in all aspects. However, the environmental aspects, global warming, and human healthcare issues are the challenge facing industries and human life, which can be like a brake to make efforts to improve digital life and machine technicity. This paper tries to produce a critical analysis of the concept "industry 4.0 revolution" based on different guidelines to show that it is an evolution of the industry coming through the development of several technologies.

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Electrical Vehicle Charging Coordination Algorithms Framework

Cited by 4 publications

References 35 publications

Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service

Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service

Robust Appointment Scheduling in Healthcare

Industry 4.0: Revolution or Evolution?

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