NSGAII enhanced with a local search for the vehicle routing problem with time windows and synchronization constraints

Haddadene, Syrine Roufaida Ait; Labadie, Nacima; Prodhon, Caroline

doi:10.1016/j.ifacol.2016.07.671

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…It is only from 2015 that we can find some papers considering several objectives, without aggregating them, and using thus multi-objective resolution methods. For the short-term planning, we can cite (Ait Haddadene et al, 2016b) and (Braekers et al, 2016) who have studied the trade-off between minimizing travel costs and maximizing the preference of patients in home care agencies, by proposing methods based on the ε-constraint approach and enumerating the Pareto Frontier, or, more recently, (Decerle et al, 2019b), who used a memetic algorithm to obtain the Pareto front for three objective functions: minimizing the total working time of the staff members, maximizing the quality of service, and minimizing the maximal working time difference among nurses and auxiliary nurses. For multiple period cases, we can cite (Rodriguez et al, 2015) who have studied the trade-off between minimizing travel costs and maximizing the staff members workload, by proposing an approximate Pareto frontier, or (Liu et al, 2018), who generated approximate Pareto fronts with three heuristics approaches in order to find a trade-off between cost and preference criteria.…”

Section: Discussion On the Objective Functionmentioning

confidence: 99%

Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

Mascolo

Martinez

Espinouse

2021

Computers & Industrial Engineering

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Section: Discussion On the Objective Functionmentioning

confidence: 99%

Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

Mascolo

Martinez

Espinouse

2021

Computers & Industrial Engineering

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“…The authors proposed a metaheuristic based on an ILS combined with the random variable neighborhood descent method (RVND) to solve the problem. A multiobjective approach to this kind of problem was addressed by [34], which sought to optimize both cost and client preferences. The authors proposed different variants of the nondominated sorting genetic algorithm (NSGA-II) to solve the problem with up to 73 clients.…”

Section: ) Vehicle Routing Problems In Hhcmentioning

confidence: 99%

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

et al. 2021

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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.

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“…e NSGA-II, a variant of the NSGA, contributes to balancing multiple objectives and generating the optimal decision on optimization problems [62,63]. Considering the proposed model, this paper improves the method of generating the initial population and using the more appropriate genetic operators based on the original NSGA-II operating process.…”

Section: E Improved Nondominated Sorting Genetic Algorithm-iimentioning

confidence: 99%

Two-Echelon Multidepot Logistics Network Design with Resource Sharing

Luo

Wang

Tang

et al. 2021

Journal of Advanced Transportation

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Resource sharing within a logistics network offers an effective way to solve problems resulting from inefficient and costly operations of individual logistics facilities. However, the existing analysis of resource sharing and profit allocation is still limited. Therefore, this study aims to model resource sharing in two-echelon delivery and pickup logistics networks to improve the overall efficiency and decrease the total network operating cost. A bi-objective integer programming model is first proposed for two-echelon collaborative multidepot pickup and delivery problems with time windows (2E-CMDPDTW) to seek the minimization of operating costs and number of vehicles. Integrating a customer clustering algorithm, a greedy algorithm, and an improved nondominated sorting genetic algorithm-II (Im-NSGA-II), a hybrid method is then designed to handle the 2E-CMDPDTW model. The customer clustering and the greedy algorithms are employed to generate locally optimized initial solutions to accelerate the calculating velocity and guarantee the diversity of feasible solutions. The Im-NSGA-II combines the order crossover operation and the polynomial mutation process to find the optimal solution of the 2E-CMDPDTW. The comparative results show that the proposed hybrid method outperforms the NSGA-II and the multiobjective genetic algorithm. Furthermore, a Shapley value method is used for allocating total profits of established alliances and finding an optimal coalition sequence of the logistics facilities joining alliances based on the strictly monotonic path strategy. Finally, a case study of 2E-CMDPDTW in Chongqing China is conducted to validate the feasibility. Results indicate that this study contributes to long-term partnerships between logistics facilities within multi-echelon logistics networks in practice and contributes to the long-term sustainability of urban logistics pickup and delivery networks’ development.

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NSGAII enhanced with a local search for the vehicle routing problem with time windows and synchronization constraints

Cited by 14 publications

References 20 publications

Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

Routing and scheduling in Home Health Care: A literature survey and bibliometric analysis

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

Two-Echelon Multidepot Logistics Network Design with Resource Sharing

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