A matheuristic approach to the integration of worker assignment and vehicle routing problems: Application to home healthcare scheduling

Moussavi, S.E.; Mahdjoub, Morad; Grunder, Olivier

doi:10.1016/j.eswa.2019.02.009

Cited by 62 publications

(20 citation statements)

References 32 publications

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“…Elbert et al [19] evaluated the effects of human behavior on the routing efficiency of order picking in a warehouse in terms of the frequently observe route deviation. Moussavi et al [20] designed a metaheuristic approach to handle the integration of worker assignment and vehicle routing problems in the context of home healthcare scheduling. Besides that, more and more researchers tend to understand and analyze the driver behaviors using different approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Regarding the different work proficiency among multiple riders, two categories of employees are assumed, i.e., beginner riders and skilled riders. For skilled employees, their productivity is postulated to follow a normal distribution as N (20,4), where the mean value is set as 20 min per order and variation is set as 4, whilst their operational cost follows a normal distribution as N(6, 1), where the average cost per order is 6 CNY. In contrast, the productivity and operational cost of beginners follow N(30, 4) and N(8, 1) respectively.…”

Section: Numerical Experimentsmentioning

confidence: 99%

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Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

2020

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The order assignment in the food delivery industry is of high complexity due to the uneven distribution of order requirements and the large-scale optimization of workforce resources. The delivery performance of employees varies in different conditions, which further exacerbates the difficulty of order assignment optimization. In this research, a non-linear multi-objective optimization model is proposed with human factor considerations in terms of both deteriorating effect and learning effect, in order to acquire the optimal solutions in practice. The objectives comprised the minimization of the operational cost in multiple periods and the workload balancing among multiple employees. The proposed model is further transformed to a standardized mixed-integer linear model by the exploitation of linearization procedures and normalization operations. Numerical experiments show that the proposed model can be easily solved using commercial optimization softwares. The results indicate that the variance of employee performance can affect the entire delivery performance, and significant improvement of workload balancing can be achieved at the price of slight increase of the operational cost. The proposed model can facilitate the decision-making process of order assignment and workforce scheduling in the food delivery industry. Moreover, it can provide managerial insights for other labor-intensive service-oriented industries.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Numerical Experimentsmentioning

confidence: 99%

Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

2020

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“…TW Simu Pre f Q Prec Reg [45] × × [46] × × × [47] × × × [48] × × [49] × × × [50] × × [47] × × × [48] × × [49] × × × [50] × × [51] × × × [52] × [53] × × × [54] × × × [55] × × [56] × × [57] × Table 4 shows that time windows and qualification are considered in the majority of the reviewed papers. However, some characteristics such as simultaneous synchronization, precedence synchronization, and periodicity have attracted less interest in the literature.…”

Section: Time Windows Simumentioning

confidence: 99%

“…Cont. [38] × [37] × [39] × × [1] × [40] × [41] × [42] × [43] × × [44] × [45] × [46] × × [47] × × [48] × × [49] × [50] × [51] × × [52] × × [53] × [54] × × [55] × × [56] × × [57] × From this literature review on vehicle routing problems related to the HHC context, It can be seen that most of proposed methods are metaheuristics and that most of papers present a mathematical method (mixed integer linear program) by mean of solvers. Furthermore, the majority of studies involving different objectives considered an aggregated function defined as a weighted sum of the considered criteria.…”

Section: Time Windows Simumentioning

confidence: 99%

“…Cont. [21] × × × [22] × × × [23] × × × [24] × × × × [25] × × × [26] × [27] × [28] × [29] × [30] × [31] × [32] × [33] × × [34] × × [35] × × [36] × × [37] × × × [38] × × [39] × × × [1] × × [40] × × [41] × × [42] × [43] × [44] × [45] × [46] × [47] × × × [48] × [49] × [50] × × × [51] × × × [52] × [53] × [54] × × × [55] × × [56] × [57] × As shown in the last table, the objective of minimizing traveling costs, waiting costs, or patient preferences is undoubtedly the most widespread in the literature. However, when multiple objective functions are handled, they are often considered within a single criterion as a weighted sum.…”

Section: Introductionmentioning

confidence: 99%

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Bicriteria Vehicle Routing Problem with Preferences and Timing Constraints in Home Health Care Services

Haddadene¹,

Labadie

Prodhon

2019

Algorithms

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Home Healthcare (HHC) is an emerging and fast-expanding service sector that gives rise to challenging vehicle routing and scheduling problems. Each day, HHC structures must schedule the visits of caregivers to patients requiring specific medical and paramedical services at home. These operations have the potential to be unsuitable if the visits are not planned correctly, leading hence to high logistics costs and/or deteriorated service level. In this article, this issue is modeled as a vehicle routing problem where a set of routes has to be built to visit patients asking for one or more specific service within a given time window and during a fixed service time. Each patient has a preference value associated with each available caregiver. The problem addressed in this paper considers two objectives to optimize simultaneously: minimize the caregivers' travel costs and maximize the patients' preferences. In this paper, different methods based on the bi-objective non-dominated sorting algorithm are proposed to solve the vehicle routing problem with time windows, preferences, and timing constraints. Numerical results are presented for instances with up to 73 clients. Metrics such as the distance measure, hyper-volume, and the number of non-dominated solutions in the Pareto front are used to assess the quality of the proposed approaches.Algorithms 2019, 12, 152 2 of 25 work (Ait Haddadene et al. [1]), the minimization of the traveling cost and the sum of non-preferences related to customers were considered as a single-objective function. The obtained results showed the conflicting nature of these criteria, which is why, we are particularly interested in solving the bi-objective version of VRPTW-SP.The problem at hand is an extension of the Vehicle Routing Problem (VRP), which is one of the most-studied combinatorial optimization problems. First introduced by Dantzig and Ramser [2], the aim of this NP-hard problem is to determine a set of minimal cost routes in which a set of customers is to be served by a fleet of vehicles based at a depot node. A detailed survey can be found in Toth and Vigo [3]. Currently, one of the most effective metaheuristics for the VRP is the hybrid genetic algorithm introduced by Vidal [4], which was latter generalized to solve more than 26 VRP variants.Among the different classes of VRP, the VRP with Time Windows (VRPTW) stands as the basis variant of our studied problem. Heuristic and metaheuristic approaches have been widely used to solve the VRPTW such as those proposed by Kindervater and Savelsbergh [5], Bräysy and Gendreau [6], Nagata [7], and Bräysy et al. [8]. In the field of healthcare, most problems are modeled as a VRPTW. In fact, the origin of vehicle routing problems in HHC systems may be linked to the door-to door-transportation of elderly or disabled persons (Dial A Ride Problems (DARP)) proposed by Bodin and Sexton [9]. A few years later, this variant was extended to the Home Healthcare (HHC) problem by Cheng and Rich [10], where caregivers are assigned to patient homes to pro...

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Home Healthcare Scheduling Activities

Jacquin¹,

Tounsi²

2022

Healthcare Systems

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In this paper, we are interested in the Home health care (HHC) scheduling problem. The HHC office needs to minimize traveling costs and to optimize caregiver assignment to patients. Scheduling patient visits have to take into account unexpected situations based on the latest scheduling information. We first analyze the HHC scheduling problem as deterministic, then discuss the dynamic challenges and propose a rescheduling approach based on genetic algorithm. A platform is designed to evaluate the proposed approach. The obtained results showed that the scheduling system is able to compute high quality schedules and can deal with urgent unpredictable situations.

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A matheuristic approach to the integration of worker assignment and vehicle routing problems: Application to home healthcare scheduling

Cited by 62 publications

References 32 publications

Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

Bicriteria Vehicle Routing Problem with Preferences and Timing Constraints in Home Health Care Services

Home Healthcare Scheduling Activities

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