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

Osorio-Mora, Alan; Soto-Bustos, Mauricio; Gatica, Gustavo; Palominos, Pedro; Linfati, Rodrigo

doi:10.1109/access.2021.3058242

Cited by 11 publications

(3 citation statements)

References 65 publications

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“…A hybrid meta-heuristic that combines a genetic algorithm and a variable neighborhood descent is proposed by them. Osorio Mora et al [ 43 ] introduce a variant of the cumulative vehicle routing problem for HHC logistics. In their version of the VRP the delayed latency is optimized.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective home health care routing: a variable neighborhood search method

2023

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Health and convenience are two indispensable indicators of the society promotion. Nowadays, to improve community health levels, the comfort of patients and those in need of health services has received much attention. Providing Home Health Care (HHC) services is one of the critical issues of health care to improve the patient convenience. However, manual nurse planning which is still performed in many HHC institutes results in a waste of time, cost, and ultimately lower efficiency. In this research, a multi-objective mixed-integer model is presented for home health care planning so that in addition to focusing on the financial goals of the institution, other objectives that can help increase productivity and quality of services are highlighted. Therefore, four different objectives of the total cost, environmental emission, workload balance, and service quality are addressed. Taking into account medical staff with different service levels, and the preferences of patients in selecting a service level, as well as different vehicle types, are other aspects discussed in this model. The epsilon-constraint method is implemented in CPLEX to solve small-size instances. Moreover, a Multi-Objective Variable Neighborhood Search (MOVNS) composed of nine local neighborhood moves is developed to solve the practical-size instances. The results of the MOVNS are compared with the epsilon-constraint method, and the strengths and weaknesses of the proposed algorithm are demonstrated by a comprehensive sensitivity analysis. To show the applicability of the algorithm, a real example is designed based on a case study, and the results of the algorithm over real data are evaluated.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-objective home health care routing: a variable neighborhood search method

2023

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“…Chen et al ( 2020 ) studied multiple emergency resource allocation problems in the context of natural disasters and concurrent events. At the same time, Osorio-Mora et al ( 2021 ) focused on taking time to propose a new mixed-integer linear programming model to solve the vehicle distribution problem. In the study of de Moura et al ( 2020 ), based on industrial disasters and natural disaster background, the corresponding logistics model was studied to solve the disaster, which has some guiding significance for emergency logistics.…”

Section: Literature Reviewmentioning

confidence: 99%

Study on optimization of multi-UAV nucleic acid sample delivery paths in large cities under the influence of epidemic environment

Han

Xiang

Cao

et al. 2023

J Ambient Intell Human Comput

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In the context of global novel coronavirus infection, we studied the distribution problem of nucleic acid samples, which are medical supplies with high urgency. A multi-UAV delivery model of nucleic acid samples with time windows and a UAV (Unmanned Aerial Vehicle) dynamics model for multiple distribution centers is established by considering UAVs’ impact cost and trajectory cost. The Golden Eagle optimization algorithm (SGDCV-GEO) based on gradient optimization and Corsi variation is proposed to solve the model by introducing gradient optimization and Corsi variation strategy in the Golden Eagle optimization algorithm. Performance evaluation by optimizing test functions, Friedman and Nemenyi test compared with Golden Jackal Optimization (GJO), Hunter-Prey Optimization (HPO), Pelican Optimization Algorithm (POA), Reptile Search Algorithm (RSA) and Golden Eagle Optimization (GEO), the convergence performance of SGDCV-GEO algorithm was demonstrated. Further, the improved RRT (Rapidly-exploring Random Trees) algorithm is used in the UAV path planning, and the pruning process and logistic chaotic mapping strategy are introduced in the path generation method. Finally, simulation experiments are conducted based on 8 hospitals and 50 randomly selected communities in the Pudong district of Shanghai, southern China. The experimental results show that the developed algorithm can effectively reduce the delivery cost and total delivery time compared with simulated annealing algorithm (SA), crow search algorithm (CSA), particle swarm algorithm (PSO), and taboo search algorithm (TS), and the developed algorithm has good uniformity, robustness, and high convergence accuracy, which can be effectively applied to the multi-UAV nucleic acid sample delivery path optimization in large cities under the influence of an epidemic environment.

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“…In [ 18 ], a novel hybrid solution procedure that merges the augmented -constraint method, optimal control theory, and dynamic programming is used to solve the developed biobjective VRP model. In [ 35 ], home healthcare (HHC) logistics as a real-life problem is discussed as a cumulative vehicle routing problem (CCVRP) in such a way that the times (especially the arrival time to the vertex for this problem minimizing the system’s delayed latency by satisfying mandatory visit times) are minimized, unlike the distance with many nonfixed depots, and travel from the depots and vertexes is inside that problem.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period

Altınöz

2022

Neural Comput & Applic

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This research is based on the capacitated vehicle routing problem with urgency where each vertex corresponds to a medical facility with a urgency level and the traveling vehicle could be contaminated. This contamination is defined as the infectiousness rate, which is defined for each vertex and each vehicle. At each visited vertex, this rate for the vehicle will be increased. Therefore time-total distance it is desired to react to vertex as fast as possible- and infectiousness rate are main issues in the problem. This problem is solved with multiobjective optimization algorithms in this research. As a multiobjective problem, two objectives are defined for this model: the time and the infectiousness, and will be solved using multiobjective optimization algorithms which are nondominated sorting genetic algorithm (NSGAII), grid-based evolutionary algorithm GrEA, hypervolume estimation algorithm HypE, strength Pareto evolutionary algorithm shift-based density estimation SPEA2-SDE, and reference points-based evolutionary algorithm.

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

Cited by 11 publications

References 65 publications

Multi-objective home health care routing: a variable neighborhood search method

Multi-objective home health care routing: a variable neighborhood search method

Study on optimization of multi-UAV nucleic acid sample delivery paths in large cities under the influence of epidemic environment

Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period

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