Examinando por Autor "Escobar, John Willmer"
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Ítem A mathematical model for scheduling and assignment of customers in hospital waste collection routes(MDPI, 2021-11) Linfati, Rodrigo; Gatica, Gustavo; Escobar, John WillmerThe collection, transport, and final disposal of hospital waste may cause contamination and disease if improperly handled. Therefore, such residues are hazardous to the health of waste collectors. These wastes are generated by public agencies, such as hospitals, family health centers, dialysis centers, and private healthcare providers. In this study, a mixed-integer linear programming model is proposed for monthly customer scheduling and route assignment. The proposed approach was fulfilled according to customers’ collection frequency, truck capacity, and customer geographical location. The proposed mathematical model successfully balanced the number of customers and the workload during each day. The effectiveness of the proposed model was tested on data obtained from a waste collection company. The model has been implemented in AMPL language, and the performance of commercial solvers, GUROBI and CPLEX, to obtain an optimal solution were tested. The results show the efficiency of the proposed approach to balance the workload concerning previous scheduling is done ad hoc at the company. The use of the formulated model provides an automatic procedure that was previously performed manually. The methodology can be adapted to other companies with similar requirements.Ítem A new genotype-phenotype genetic algorithm for the two-dimensional strip packing problem with rotation of 90°(Pontificia Universidad Javeriana, 2016-01) Gatica, Gustavo; Villagrán, Gonzalo; Contreras-Bolton, Carlos; Linfati, Rodrigo; Escobar, John WillmerGiven a set of rectangular pieces and a fixed width with infinite length, the strip-packing problem (SPP) of two dimensions (2D), with a rotation of pieces in 90° consists of orthogonally placing all the pieces on the strip, without overlapping them, minimizing the height of the strip used. Several algorithms have been proposed to solve this problem, being Genetic Algorithms one of the most popular approach due to it effectiveness solving NP-Hard problems. In this paper, three binary representations, and classic crossover and mutation operators are introduced. A comparison of the three binary representations on a subset of benchmarking instances is performed. The representation R2 outperforms the results obtained by representation R1 and R3. Indeed, some of the bestknown results found by previous published approaches are improved. © 2015, Pontificia Universidad Javeriana. All rights reserved.