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David Álvarez-Martínez

Publications and source records attributed to David Álvarez-Martínez.

2 recordsLinked to original sources

Integrating and Comparing Radiality Constraints for Optimized Distribution System Reconfiguration

The reconfiguration of electrical power distribution systems is a crucial optimization problem aimed at minimizing power losses by altering the system topology through the operation of interconnection switches. This problem, typically modelled as a mixed integer nonlinear program demands high computational resources for large scale networks and requires specialized radiality constraints for maintaining the tree like structure of distribution networks. This paper presents a comprehensive analysis that integrates and compares the computational burden associated with different radiality constraint formulations proposed in the specialized literature for the reconfiguration of distribution systems. By using consistent hardware and software setups, we evaluate the performance of these constraints across several well known test cases. Our findings reveal significant differences in computational efficiency depending on the chosen set of radiality constraints, providing valuable insights for optimizing reconfiguration strategies in practical distribution networks.

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A GRASP algorithm for the Meal Delivery Routing Problem

With the escalating demand for meal delivery services, this study delves into the Meal Delivery Routing Problem (MDRP) within the context of last-mile logis-tics. Focusing on the critical aspects of courier allocation and order fulfillment, we introduce a novel approach utilizing a GRASP metaheuristic. The algorithm optimizes the assignment of couriers to orders, considering dynamic factors such as courier availability, order demands, and geographical locations. Real-world in-stances from a Colombian delivery app form the basis of our computational anal-ysis. Calibration of GRASP parameters reveals a delicate trade-off between solu-tion quality and computational time. Comparative results with a simulation-optimization based study underscore GRASP's competitive performance, demon-strating strengths in fulfilling orders and routing efficiency across diverse in-stances. This research enhances operational efficiency in the burgeoning food de-livery industry, shedding light on practical algorithms for last-mile logistics opti-mization.

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