Open Access
Robots for elderly care: review, multi-criteria optimization model and qualitative case study
(MDPI, 2023) Sawik, Bartosz; Tobis, Sławomir; Baum, Ewa; Suwalska, Aleksandra; Kropińska, Sylwia; Stachnik, Katarzyna; Pérez Bernabeu, Elena; Cildoz Esquíroz, Marta; Agustín Martín, Alba; Wieczorowska-Tobis, Katarzyna.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This paper focuses on three areas: the first is a review of current knowledge about social and service robots for elderly care. The second is an optimization conceptual model aimed at maximizing the efficiency of assigning robots to serve the elderly. The proposed multi-criteria optimization model is the first one proposed in the area of optimization for robot assignment for the elderly with robot utilization level and caregiver stress level. The third is the findings of studies on the needs, requirements, and adoption of technology in elderly care. We consider the use of robots as a part of the ENRICHME project for long-term interaction and monitoring of older persons with mild cognitive impairment, to optimize their independence. Additionally, we performed focus group discussions (FGD) to collect opinions about robot-related requirements of the elderly and their caregivers. Four FDGs of six persons were organized: two comprising older adults, and two of the other formal and informal caregivers, based on a detailed script. The statements of older participants and their caregivers were consistent in several areas. The analysis revealed user characteristics, robot-related issues, functionality, and barriers to overcome before the deployment of the robot. An introduction of the robot must be thoroughly planned, include comprehensive pre-training, and take the ethical and practical issues into account. The involvement of future users in the customization of the robot is essential.
Open Access
Multi-criteria optimization for fleet size with environmental aspects
(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Institute of Smart Cities - ISC
This research concerns multi-criteria vehicle routing problems. Mathematical models are formulated with mixed-integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain.We consider heterogeneous fleet of trucks. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Companies planningdelivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, utilization of fuel, carbon emission and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution.
Open Access
A multicriteria analysis for the green VRP: a case discussion for the distribution problem of a Spanish retailer
(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise.

Sawik, Bartosz

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