A Greedy Randomized Adaptive Search With Probabilistic Learning for solving the Uncapacitated Plant Cycle Location Problem

In this paper, we address the Uncapacitated Plant Cycle Location Problem. It is a location-routing problem aimed at determining a subset of locations to set up plants dedicated to serving customers. We propose a mathematical formulation to model the problem. The high computational burden required by the formulation when tackling large scenarios encourages us to develop a Greedy Randomized Adaptive Search Procedure with Probabilistic Learning Model. Its rationale is to divide the problem into two interconnected sub-problems. The computational results indicate the high performance of our proposal in terms of the quality of reported solutions and computational time. Specifically, we have overcome the best approach from the literature on a wide range of scenarios.</p

The Multi-Depot Cumulative Vehicle Routing Problem With Mandatory Visit Times and Minimum Delayed Latency

This paper introduces a novel variant of the cumulative vehicle routing problem (CCVRP) that deals with home health care (HHC) logistics. It includes multiple nonfixed depots and emergency trips from patients to the closest depot. The aim is to minimize the system's delayed latency by satisfying mandatory visit times. Delayed latency corresponds to caregivers' total overtime hours worked while visiting patients. A new mixed-integer linear programming model is proposed to address this problem. Computational experiments, with more than 165 new benchmark instances, are carried out using the CPLEX and Gurobi MIP solvers. The results indicate that patients' geographical distribution directly impacts the complexity of the problem. An analysis of the model parameters proves that instances with more depots/vehicles or longer workdays are significantly easier to solve than are original cases. The results show that Gurobi outperforms CPLEX in 55% of the instances analyzed, while CPLEX performs better in only 16% of them. To the best of our knowledge, this is the first VRP that minimizes delayed latency and the first HHC routing study to use a cumulative objective function

A POPMUSIC approach for the Multi-Depot Cumulative Capacitated Vehicle Routing Problem

The Multi-Depot Cumulative Capacitated Vehicle Routing Problem is a variation of the recently proposed Capacitated Cumulative Vehicle Routing Problem, where several depots can be considered as starting points of routes. Its objective aims at minimizing the sum of arrival times at customers for providing service. Practical considerations imply to address the delivery of customers from multiple depots where the service quality level depends on the customer waiting time and the delivering vehicles may be able to depart from different points. Those scenarios require theoretical models to support the decision-making process as well as for measuring the quality of the solutions provided by approximate approaches. In the present work, we formalize this new problem variant by means of a mathematical formulation and propose a matheuristic approach (POPMUSIC) for solving it