Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions

Luo, Hongyuan; Dridi, Mahjoub; Grunder, Olivier

doi:10.1007/978-3-030-45715-0_11

Cited by 1 publication

(2 citation statements)

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“…Although the authors considered the speed factor, the speed was set as a constant. Luo et al (2019) also studied HHC scheduling considering the carbon emissions. However, in this research, the authors also consider the speed as a constant.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In order to demonstrate the effectiveness of the proposed HACO algorithm on the studied problem with only one speed level, we set several comparison methods, respectively, the classical ACO algorithm (Luo et al 2019), MA (Nalepa and Blocho 2016;Decerle et al 2018) which has been successfully applied to many routing related researches, and an exact method.…”

Section: Experiments For the Simplified Problemmentioning

confidence: 99%

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An ACO-based heuristic approach for a route and speed optimization problem in home health care with synchronized visits and carbon emissions

2021

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The growing concern about the influences of anthropogenic pollutions has forced researchers and scholars to study the environmental concerns. This paper addresses a joint daily route and speed optimization problem in home health care (HHC) with the constraints of synchronized visits and carbon emissions. In this work, the aim is to design a reasonable logistics route with the objective of minimizing the carbon emissions, which has a linear relationship with fuel consumption. This goal can reduce environmental pollution while optimizing operating costs for the HHC company. This paper formulated the problem as a mixed-integer programming (MIP) model and used the Gurobi solver to solve the MIP model with a time limit of 1 h. However, the method based on the MIP model is difficult to solve large-scale instances. Therefore, this paper proposed an ant colony optimization (ACO)-based heuristic approach improved by local search for this problem with large-scale instances. The minimal carbon emissions of each route is calculated by a dynamic programming (DM) algorithm. We designed three kinds of experiments to test the proposed approach, including the basic vehicle routing problem with time window (VRPTW), the studied problem with one speed and the studied problem with two speeds. The experimental results highlight the effectiveness and efficiency of the proposed approach. KeywordsHome health care • Synchronized visits • Carbon emissions • ACO-based heuristic • Dynamic programming

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Section: Literature Reviewmentioning

confidence: 99%