Pharmaceutical R &amp; D pipeline management under trial duration uncertainty

Gokalp, Elvan; Branke, Juergen

doi:10.1016/j.compchemeng.2020.106782

Cited by 8 publications

(1 citation statement)

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“…Through many applications, such as planning of energy resources (Powell et al, 2012;Sedighizadeh et al, 2019), trading (Abbaszadeh et al, 2018) and pharmaceuticals (G€ okalp & Branke, 2020), ADP has proved to be useful in dealing with complex stochastic and dynamic problems, which makes it suitable for the problem considered in this paper. Although, the OR literature on humanitarian operations is well developed, as mentioned above, studies tend to rely on traditional techniques such as integer programming.…”

Section: Literature Reviewmentioning

confidence: 99%

Capacity management of migrant accommodation centers using approximate dynamic programming

Gokalp

Cakir

Kougkoulos

2021

Journal of the Operational Research Society

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Irregular migration has become a major macro-economic and political challenge. Due to rising political conflicts and income inequality across the world, the number of migrants is expected to increase exponentially over the coming decade. Thus, it is of critical importance to effectively use the limited resources allocated to humanitarian operations for irregular migration. In this paper we model the problem of capacity management and migrant transfers within a network of migrant accommodation centres with stochastic dynamic programming. Our study extends the literature on stochastic modelling and humanitarian operations by applying Approximate Dynamic Programming (ADP) into a new context. The model is translatable in other similar migratory routes and locations around the world where governments need to deal with uncertain numbers of irregular migrants. We test our approach on five Greek islands which have been the main migrant arrival points during the European Migrant Crisis. The results show that ADP provides a better computational performance than a simple myopic heuristic. The sensitivity analysis gives insights to the decision-makers about the impact of parameter values on the policies.

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