A vehicle routing problem for biological sample transportation in healthcare: mathematical formulations and a metaheuristic approach (original) (raw)
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A Vehicle Routing Problem for the Collection of Medical Samples at Home: Case Study of Morocco
International Journal of Advanced Computer Science and Applications, 2021
This paper aims to solve the problem of sampling and collecting blood and/ or urine tubes from sick people at home via a medical staff (nurse/ caregiver) to the laboratory in an optimal way. To ensure good management, several constraints must be taken into account, namely, staff schedules, patient preferences, the maximum delay time for a blood sample, etc. This problem is considered as a vehicle routing problem with time windows, preference and priority according to urgent cases. We first proposed a mathematical formulation of the problem by using a mixed integer linear programming (MILP) as well as various metaheuristics. Also, we applied this method to a real instance of a laboratory in Morocco (Témara) named Laboratory BioGuich, which gave the most optimal results.
Journal of the Operational Research Society, 2019
This paper addresses a new version of the biomedical sample transportation problem, as a vehicle routing problem with precedence constraints arising in the context of healthcare logistics, and proposes an iterated local search algorithm to solve it. This new version is more realistic and complex since it considers the collection centers' opening hours and the moment at which they are visited as decision variables, granting additional flexibility to elaborate more efficient routes. Indeed, this problem is harder to model and to solve than its previous version because the constraint on the short samples' lifetime leads to interdependency between successive pickups at each collection center. A metaheuristic is thus proposed to solve real-life instances. Numerical experiments confirm (1) the value of simultaneously planning routes, opening hours, and visits' hours (which is new in the literature) and (2) the efficiency of the proposed algorithm to solve this problem.
Modeling a production-inventory-routing problem of blood products using heuristic solution methods
Journal of Intelligent & Fuzzy Systems, 2019
Blood and blood products are vital resources for the surgery and the treatment of certain diseases. As a scarce and perishable resource, they require sophisticated management to minimize waste in order to address this challenge, the present study revolves around the idea of the management of the production, supply and distribution of blood products. In this research, two questions of robust and flexible have been investigated for the production, inventory and routing blood products. The flexibility is incorporated into the problem through introducing the possibility of sharing inventory among network entities by transferring blood products between hospitals and also the possibility of meeting a blood group's need with another compatible blood type or replacement. The problem is then solved by heuristic (local search) and meta-heuristic (Adaptive Large Neighborhood Search (ALNS)) algorithms, which are the methods of choice in particular for NP-hard problems. Finally, the results obtained from the two algorithms are compared it is shown that the heuristic algorithm outperforms the Adaptive Large Neighborhood Search (ALNS) in both models, that can lead to reduction is cost and required transitions.
Studies in Health Technology and Informatics, 2024
Healthcare processes are complex and involve uncertainties to influence the service quality and health of patients. Patient transportation takes place between the hospitals or between the departments within the hospital (i.e., Inter-or Intra-Hospital Transportation respectively). The focus of our paper is route planning for transporting patients within the hospital. The route planning task is complex due to multiple factors such as regulations, fairness considerations (i.e., balanced workload amongst transporters), and other dynamic factors (i.e., transport delays, wait times). Transporters perform the physical transportation of patients within the hospital. In principle, each job allocation respects the transition time between the subsequent jobs. The primary objective was to determine the feasible number of transporters, and then generate the route plan for all determined transporters by distributing all transport jobs (i.e., from retrospective data) within each shift. Secondary objectives are to minimize the sum of total travel time and sum of total idle time of all transporters and minimize the deviations in total travel time amongst transporters. Our method used multi-staged Local Search Metaheuristics to attain the primary objective. Metaheuristics incorporate Mixed Integer Linear Programming to allocate fairly the transport jobs by formulating optimization constraints with bounds for satisfying the secondary objectives. The obtained results using formulated optimization constraints represent better efficacy in multi-objective route planning of Intra-Hospital Transportation of patients.
Jurnal Logistik Indonesia
The process of distributing blood bags by the Indonesian Red Cross (PMI) DKI Jakarta uses route selection preferences by ambulance drivers. Basically, this routing problem can impact other aspects such as additional costs, distribution time, fuel use, carbon emissions, and others, so this research needs to propose the best route to minimize travel distance. There are several Hospital Blood Banks (BDRS) in Jakarta that do not receive blood bags at the right time. As an organization authorized to provide blood bag supply, the PMI must distribute blood bag using the 7R concept (Right Time, Right Place, Right Quantity, Right Quality, Right Cost, Right Condition, and Right People). The PMI also has to consider that blood bags are classified as perishable items that need to require fast and precise handling. Therefore, it is necessary to optimize the blood distribution by minimizing travel distance. The optimization model used is the Vehicle Routing Problem (VRP) with AMPL software compar...
2021
This case study investigated blood distribution on a Blood Transfusion Unit at the Red Cross in Indonesia. This unit facilitates health services in organizing blood donations, blood examinations, and blood distribution for patients. Currently, the management of blood distribution from the Blood Transfusion Unit to the hospital does not consider the optimal distance and route of blood distribution. In addition, this case study shows that 19 hospitals request types of blood to the Blood Transfusion Units. This study aims to determine the optimal route of blood distribution in the Blood Transfusion Unit. This study needs to solve the Vehicle Routing Problem by adopting the Sweep Algorithm to minimize the distance of blood distribution and determine the distribution route. Optimization of blood distribution found a reduction in the distance by 57% with a reduction in time of 58%. Further research is suggested to determine the scheduling of ordering blood requirements to obtain optimal results.
IOP Conference Series: Materials Science and Engineering
The blood service is a health service that utilizes human blood as basic material with humanitarian purposes, not for commercial one. Indonesian hospital ability in blood transfusions is generally still low, especially in terms of blood supply adequacy. In fact, there are still some provinces that experience excess blood supply while many other provinces experience a shortage of blood supply. The Blood Bank in Jakarta has the highest excess blood supply. Therefore, the blood can be transferred evenly from one province to another nearby province. The aim of this paper is to determine the allocation and the route of blood distribution to achieve the minimum travel times. Some variations in travel time are difficult to predict, so we take into account the stochastic properties of them. The effectiveness of blood distribution is very dependent on the accuracy of the target number of beneficiaries and the accuracy of the number of blood bags received in distribution activities. Meanwhile, the efficiency of blood bag distribution is measured by distribution routes that are directly related to transportation costs. This study uses a two-step optimization model to reach optimality. The first step is utilizing the transportation model to make sure the destination points are only the fastest to arrive. The second step is making use of the capacitated vehicle routing problem to ensure the routing is global optimal. This model successfully creates better blood demand fulfillment while minimizing transportation cost.
Vehicle Routing Problem for Blood Mobile Collection System with Stochastic Supply
2018
The mobile collection system of blood products is considered in this study. Blood centers often use bloodmobiles that park near crowded places where donors can donate blood directly. We propose the use of additional vehicles, called shuttles, that pick up the collected blood by the bloodmobiles. Hence, bloodmobiles can continue their tours without having to return to the blood center. The system manager must decide the set of sites to visit by the bloodmobiles among a group of potential sites, and to determine the tours of the vehicles responsible for this operation. In this paper, the blood mobile collection system is modelled as a vehicle routing problem with profits. The objective is to minimize the total routing, wastage and shortage costs. Each collection site has a random potential blood quantity that is modeled as a stochastic profit which can be collected by a vehicle when it visits this site. A Two-Stage Stochastic Model with recourse is developed to represent the problem u...
IFAC-PapersOnLine, 2019
Home health care (HHC) companies provide a wide range of medical and social services to patients in their own homes to help them rehabilitate after illness or injury. Providing high-quality services and reducing operating costs are accessible through proper planning of different sectors of HHC companies. This study presents a mathematical model integrated with real-life constraints to address a home health care routing and scheduling problem (HHCRSP). The planning takes into account temporal precedence and synchronization constraints and limited allowable times for transferring collected biological samples to the laboratory in the pickup and delivery environment. This problem is a new variant of the vehicle routing problem with time windows (VRPTW) with the aim of minimizing the cost related to the transportation and the idle time of caregivers by assigning proper caregivers with required qualifications to patients based on their disjunctive needs. Simulated annealing (SA) and tabu search (TS) are two meta-heuristics applied in two phases for each instance to schedule primary tasks in the first step, and then synchronized services in the next phase.