Biomedical sample transportation in the province of Quebec: a case study

Anaya-Arenas, Ana María; Coelho, Leandro C.; Ruiz, Angel

doi:10.1080/00207543.2015.1018455

Cited by 14 publications

(4 citation statements)

References 25 publications

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“…The algorithm was coded on VB.NET and executed on a PC with an Intel® Core™ i7-6700 CPU @3.4 GHz (2 processors), 16 GB of RAM. We solved the set of 38 instances proposed in Anaya-Arenas et al (2016). Instances are separated in two groups.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…The biomedical sample transportation problem (BSTP), as presented by Anaya-Arenas, Chabot, Renaud & Ruiz (2016), is a vehicle routing problem (VRP) that aims to create a transportation plan to pick up perishable items (biomedical samples) at given locations, referred to as specimen collection centers (SCC), and to take them to facilities possessing the adequate treatment equipment (the laboratories or labs). The centralization of samples' analysis at a single lab brings material advantages from both economic and quality control perspectives.…”

Section: Introductionmentioning

confidence: 99%

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An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups

Anaya-Arenas

Prodhon

Renaud

et al. 2019

Journal of the Operational Research Society

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An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups Anaya-Arenas et al. 2019 [2] An Iterated Local Search for the Biomedical Sample Transportation Problem with Multiple and Interdependent Pickups 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 health care 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 visit hours (which is new in the literature) and (2) the efficiency of the proposed algorithm to solve this problem.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups

Anaya-Arenas

Prodhon

Renaud

et al. 2019

Journal of the Operational Research Society

Self Cite

View full text Add to dashboard Cite

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“…with the similar study by Comtet et al [32] who also noted large benefits in journey times but suggested there may be concerns over a need for a backup system. A more frequent and expeditious service has the potential to provide three benefits: (i) better workflow management and control for laboratory staff and/or equipment of samples arriving for analysis; (ii) samples spend less time subjected to uncontrolled in-vehicle conditions, which may be harmful to samples (e.g., excessive temperature or vibration conditions) and affect the integrity of analysis results [52,82,83]; and (iii) reduced bleed-to-diagnosis times, which would be advantageous for any time-critical samples. Blood samples taken from cancer patients to inform the prescription of chemotherapy treatments, a significant proportion of which are bespoke manufactured for their specific needs a few hours prior to administration are a good example.…”

Section: Plos Onementioning

confidence: 99%

Integrating drones into NHS patient diagnostic logistics systems: Flight or fantasy?

et al. 2022

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Healthcare accounts for approximately 5% of emissions in developed nations, and the public healthcare provider in the United Kingdom (UK), the National Health Service (NHS), has set a target to reach net-zero emissions by 2040 without detriment to its quality of patient care. With Uncrewed Aerial Vehicles (UAVs; a.k.a. drones, UAS, or RPAS) starting to be used in healthcare systems outside the UK, there is interest in how they could be integrated into NHS operations to transport diagnostic specimens. Reflecting on a business-as-usual analysis of current NHS diagnostic specimen logistics across the Solent region (southern UK), this paper critically evaluates the practical reality of integrating UAV deliveries of this commodity, identifying the benefits and challenges that must be addressed to realise commercial services, including dangerous goods legislation, cargo stability, routing, and weather. In the analysis, 14 out of 79 surgeries could be realistically served by a 5m wingspan vertical take-off/landing (VTOL) UAV: seven directly, and seven via ground-based transfers. The results suggested that an average of 1,628 samples could be served by UAV each week, resulting in 42 flights/week with 10 taxi services to cover periods where weather limited flying. This equated to an approximate total service cost of £2,964/week if regulations develop to relax UAV personnel constraints. The introduction of UAVs reduced the marginal external costs (greenhouse gas emissions, congestion, and air pollution) by £196 per week and cut travel times to UAV served sites by 72% (weather permitting). Tailpipe emissions (excl. taxis), vehicle-kilometres travelled, and van costs were reduced by 20%, 20%, and 23% (respectively), but the overall system cost increased by 56%. Whilst this increase is likely to make the introduction of UAV services financially challenging, the benefits in terms of emissions and journey time savings may offset some of the additional cost and warrant further investigation.

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“…Hong Kong'daki bir hastanede yaşlı ve engelli hastaların nakil işlemleri problemini ÇTARP olarak modellemişler, matematiksel modelin yanısıra yığın tabanlı sezgisel bir algoritma da önerilmiştir. Bu alanda diğer bir çalışma ise Anaya-Arenas vd [23]. tarafından yapılmış olup, ÇTARP olarak ele aldıkları sistem için iki farklı model geliştirmişlerdir.…”

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Evde sağlık hizmetlerinde çok amaçlı, çok turlu ve zaman pencereli rotalama problemi için hedef programlama yaklaşımı

Dengiz

Atalay

Altıparmak

2021

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Dünyayı etkileyen salgın hastalıklar, nüfus artışı, gelişen teknolojiler sağlık sektöründeki hizmetlerin yapısını da değiştirmektedir. Sağladığı avantajlar nedeniyle evde sağlık hizmetleri (ESH) hastalar tarafından her geçen gün daha fazla talep edilmektedir. Bu sebeple araştımacıların Evde Sağlık Hizmetleri Rotalama Problemine (ESHRP) ilgisi artmaktadır. Bu çalışmada, Ankara’da ESH veren bir Devlet Hastanesinin ilgili biriminde yapılan incelemelere dayalı olarak ESHRP tanımlanmıştır. Ele alınan hastanede kaynakların kısıtlı olmasından dolayı araçların birden fazla kullanılması gerekmektedir. Dolayısıyla, ESHRP çok turlu olarak dikkate alınmıştır. Ayrıca, hastaların taleplerinin zamanında karşılanmasını sağlamak amacıyla problem zaman pencereli bir yapıdadır. Bunun yanısıra, ESHRP'de karşılanan hasta taleplerinin enbüyüklenmesi ve çevresel etkilerin azaltılması önemli iki amaçtır. Çevresel etkilerin azaltılması ESH’de kullanılan araçların karbon salınımının enküçüklenmesi ile sağlanabilir. Bu nedenle bu çalışmada ele alınan problem çok amaçlı, çok turlu ve zaman pencereli evde sağlık hizmetleri rotalama problemi (ÇTZP-ESHRP) olarak tanımlanmıştır. Problemin çözümü için ağırlıklı hedef programlama (HP) metodu kullanılmıştır. Ankara’da hizmet veren bir hastaneden elde edilen verilere dayalı olarak test problemleri üretilmiş ve senaryo analizi ile bulunan çözümler karar alma sürecine yön verecek şekilde değerlendirilmiştir.

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Biomedical sample transportation in the province of Quebec: a case study

Cited by 14 publications

References 25 publications

An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups

An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups

Integrating drones into NHS patient diagnostic logistics systems: Flight or fantasy?

Evde sağlık hizmetlerinde çok amaçlı, çok turlu ve zaman pencereli rotalama problemi için hedef programlama yaklaşımı

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