1. |
- Wiklund, Stig Johan, et al.
(author)
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Replenishing the pipeline: A quantitative approach to optimising the sourcing of new projects
- 2023
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In: Pharmaceutical Statistics. - 1539-1604 .- 1539-1612. ; In Press
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Journal article (peer-reviewed)abstract
- Large pharmaceutical companies maintain a portfolio of assets, some of which are projects under development while others are on the market and generating revenue. The budget allocated to R&D may not always be sufficient to fund all the available projects for development. Much attention has been paid to the selection of optimal subsets of available projects to fit within the available budget. In this paper, we argue the need for a forward-looking approach to portfolio decision-making. We develop a quantitative model that allows the portfolio management to evaluate the need for future inflow of new projects to achieve revenue at desired levels, often aspiring to a certain annual revenue growth. Optimisation methods are developed for the presented model, allowing an optimal choice of number, timing and type of projects to be added to the portfolio. The proposed methodology allows for a proactive approach to portfolio management, prioritisation, and optimisation. It provides a quantitatively based support for strategic decisions regarding the efforts needed to secure the future development pipeline and revenue stream of the company.
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2. |
- Almgren, Torgny, 1962, et al.
(author)
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Optimization models for improving periodic maintenance schedules by utilizing opportunities
- 2012
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In: Proceedings of 4th Production and Operations Management World Conference, July 2012.
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Conference paper (peer-reviewed)abstract
- We present mathematical models for finding optimal opportunistic maintenance schedules for systems, in which components are assigned maximum replacement intervals. Our mod- els are applied to safety-critical components in an aircraft engine, for which maintenance opportunities naturally arise since entire modules are sent to the workshop when mainte- nance is required on one or more components. Case study results illustrate the advantage of the mathematical models over simpler policies, the benefit of coordinating the maintenance in economically dependent systems, and that our models can be utilized also for strategic investment decision support.
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3. |
- Almgren, Torgny, 1962, et al.
(author)
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The opportunistic replacement problem: theoretical analyses and numerical tests
- 2012
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In: Mathematical Methods of Operations Research. - : Springer Science and Business Media LLC. - 1432-2994 .- 1432-5217. ; 76:3, s. 289-319
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Journal article (peer-reviewed)abstract
- We consider a model for determining optimal opportunistic maintenance schedules with respect to a maximum replacement interval. This problem generalizes that of Dickman et al. (J Oper Res Soc India 28:165–175, 1991) and is a natural starting point for modelling replacement schedules of more complex systems. We show that this basic opportunistic replacement problem is NP-hard, that the convex hull of the set of feasible replacement schedules is full-dimensional, that all the inequalities of the model are facet-inducing, and present a new class of facets obtained through a {0,1/2}-Chvátal–Gomory rounding. For costs monotone with time, a class of elimination constraints is introduced to reduce the computation time; it allows maintenance only when the replacement of at least one component is necessary. For costs decreasing with time, these constraints eliminate non-optimal solutions. When maintenance occasions are fixed, the remaining problem is stated as a linear program and solved by a greedy procedure. Results from a case study on aircraft engine maintenance illustrate the advantage of the optimization model over simpler policies. We include the new class of facets in a branch-and-cut framework and note a decrease in the number of branch-and-bound nodes and simplex iterations for most instance classes with time dependent costs. For instance classes with time independent costs and few components the elimination constraints are used favorably. For fixed maintenance occasions the greedy procedure reduces the computation time as compared with linear programming techniques for all instances tested.
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5. |
- Berman, Robert, 1976, et al.
(author)
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Propagation of chaos, wasserstein gradient flows and toric Kähler-Einstein metrics
- 2018
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In: Analysis and PDE. - : Mathematical Sciences Publishers. - 2157-5045 .- 1948-206X. ; 11:6, s. 1343-1380
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Journal article (peer-reviewed)abstract
- Motivated by a probabilistic approach to Kähler-Einstein metrics we consider a general nonequilibrium statistical mechanics model in Euclidean space consisting of the stochastic gradient flow of a given (possibly singular) quasiconvex N-particle interaction energy. We show that a deterministic "macroscopic" evolution equation emerges in the large N-limit of many particles. This is a strengthening of previous results which required a uniform two-sided bound on the Hessian of the interaction energy. The proof uses the theory of weak gradient flows on the Wasserstein space. Applied to the setting of permanental point processes at "negative temperature", the corresponding limiting evolution equation yields a driftdiffusion equation, coupled to the Monge-Ampère operator, whose static solutions correspond to toric Kähler-Einstein metrics. This drift-diffusion equation is the gradient flow on the Wasserstein space of probability measures of the K-energy functional in Kähler geometry and it can be seen as a fully nonlinear version of various extensively studied dissipative evolution equations and conservation laws, including the Keller-Segel equation and Burger's equation. In a companion paper, applications to singular pair interactions in one dimension are given.
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6. |
- Gustavsson, Emil, 1987, et al.
(author)
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Preventive maintenance scheduling of multi-component systems with deterioration costs
- 2012
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Other publication (other academic/artistic)abstract
- We introduce the preventive maintenance scheduling problem with interval costs (PMSPIC), which is to schedule preventive maintenance of components of a system over a finite discretized time horizon, given a common set-up cost and component costs dependent on the lengths of the maintenance intervals. We present a 0-1 integer linear programming (0-1 ILP) model for the PMSPIC which was originally presented by Joneja (1990) to model the joint replenishment problem. We show that most of the integrality constraints can be relaxed and that the linear inequality constraints define facets of the convex hull of the feasible set. We present three applications demonstrating that the PMSPIC can be used to model several types of maintenance problems with deterioration costs. The first considers rail grinding. If the interval between the grinding occasions increases, then the sizes of the rail cracks increase, which implies that more grinding passes must be performed, generating a higher maintenance cost. We presume a deterministic model for crack growth and optimize the scheduling of the rail grinding on a set of track sections. Our second application concerns two approaches for the scheduling of component replacements in aircraft engines. In the first approach a bi-objective problem, simultaneously minimizing the cost for the scheduled preventive maintenance and the probability of unexpected stops, is formulated. The second approach considers the minimization of the sum of costs of preventive and expected corrective maintenance, without rescheduling. We also demonstrate that if rescheduling is allowed, then the 0-1 ILP model can be used as a policy by re-optimizing the schedule at a component failure, thus utilizing the opportunity for preventive maintenance. We evaluate the use of such a strategy in a simulation of the engine. The third approach considers components’ replacement in wind mills in a wind farm, extending the PMSPIC to consider several systems with a joint set-up cost. As for the aircraft engine application, we use the 0-1 ILP model as a policy for deciding upon replacement decisions allowing for rescheduling, and evaluate it by simulating the joint system. In each of the three applications, the use of the 0-1 ILP model is compared with age or constantinterval policies, resulting in a reduction of maintenance costs by up to 15% compared with the respective best simple policy.
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7. |
- Gustavsson, Emil, 1987, et al.
(author)
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Preventive maintenance scheduling of multi-component systems with interval costs
- 2014
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In: Computers & industrial engineering. - : Elsevier BV. - 0360-8352. ; 76, s. 390-400
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Journal article (peer-reviewed)abstract
- We introduce the preventive maintenance scheduling problem with interval costs (PMSPIC), which is to schedule preventive maintenance (PM) of the components of a system over a finite and discretized time horizon, given a common set-up cost and component costs dependent on the lengths of the maintenance intervals. We present a 0–1 integer linear programming (0–1 ILP) model for the PMSPIC; the model is identical to that presented by Joneja (1990) for the joint replenishment problem within inventory management. We study this model from a polyhedral and exact solutions’ point of view, as opposed to previously studied heuristics (e.g. Boctor, Laporte, & Renaud, 2004; Federgruen & Tzur, 1994; Levi, Roundy, & Shmoys, 2006; Joneja, 1990).We show that most of the integrality constraints can be relaxed and that the linear inequality constraints define facets of the convex hull of the feasible set. We further relate the PMSPIC to the opportunistic replacement problem, for which detailed polyhedral studies were performed by Almgren et al. (2012a). The PMSPIC can be used as a building block to model several types of maintenance planning problems possessing deterioration costs. By a careful modeling of these costs, a polyhedrally sound 0–1 ILP model is used to find optimal solutions to realistic-sized multi-component maintenance planning problems. The PMSPIC is thus easily extended by side constraints or to multiple tiers, which is demonstrated through three applications; these are chosen to span several levels of unmodeled randomness requiring fundamentally different maintenance policies, which are all handled by variations of our basic model. Our first application considers rail grinding. Rail cracks increase with increasing intervals between grinding occasions, implying that more grinding passes must be performed—thus generating higher costs. We optimize the grinding schedule for a set of track sections presuming a deterministic model for crack growth; hence, no corrective maintenance (CM) will occur between the grinding occasions scheduled. The second application concerns two approaches for scheduling component replacements in aircraft engines. The first approach is bi-objective, simultaneously minimizing the cost for the scheduled PM and the probability of unexpected stops. In the second approach the sum of costs for PM and expected CM—without rescheduling—is minimized. When rescheduling is allowed, the 0–1 ILP model is used as a policy by re-optimizing the schedule at a component failure, which then constitutes an opportunity for PM. The policy manages the trade-off between costs for PM and unplanned CM and is evaluated in a simulation of the engine. The third application considers components’ replacement in wind mills in a wind farm, extending the PMSPIC to comprise multiple tiers with joint set-up costs. Due to the large number of components unexpected stops occur frequently, thus calling for a dynamic rescheduling, which is evaluated through a simulation of the system. In each of the three applications, the use of the 0-1 ILP model is compared with age or constant-interval policies; the maintenance costs are reduced by up to 16% as compared with the respective best simple policy. The results are strongest for the first two applications, possessing low levels of unmodeled randomness.
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9. |
- Hartley, Philippa, et al.
(author)
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SKA Science Data Challenge 2: analysis and results
- 2023
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In: Monthly Notices of the Royal Astronomical Society. - 0035-8711 .- 1365-2966. ; 523:2, s. 1967-1993
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Journal article (peer-reviewed)abstract
- The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarize the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterize 233 245 neutral hydrogen (H i) sources in a simulated data product representing a 2000 h SKA-Mid spectral line observation from redshifts 0.25-0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, 'reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy - which combined predictions from two independent machine learning techniques to yield a 20 per cent improvement in overall performance - underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical data sets.
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10. |
- Hultgren, Jakob, 1986, et al.
(author)
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An Optimal Transport Approach to Monge-Ampère Equations on Compact Hessian Manifolds
- 2019
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In: Journal of Geometric Analysis. - : Springer Science and Business Media LLC. - 1050-6926 .- 1559-002X. ; 29:3, s. 1953-1990
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Journal article (peer-reviewed)abstract
- In this paper we consider Monge–Ampère equations on compact Hessian manifolds, or equivalently Monge–Ampère equations on certain unbounded convex domains in Euclidean space, with a periodicity constraint given by the action of an affine group. In the case where the affine group action is volume preserving, i.e., when the manifold is special, the solvability of the corresponding Monge–Ampère equation was first established by Cheng and Yau using the continuity method. In the general case we set up a variational framework involving certain dual manifolds and a generalization of the classical Legendre transform. We give existence and uniqueness results and elaborate on connections to optimal transport and quasi-periodic tilings of convex domains.
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