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- Almgren, Torgny, 1962, et al.
(författare)
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The opportunistic replacement problem: analysis and case studies
- 2011
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We consider an optimization model for determining optimal opportunistic maintenance (that is, component replacement) schedules when data is deterministic. This problem generalizes that of Dickman, Epstein, and Wilamowsky [21] and is a natural starting point for the modelling of replacement schedules when component lives are non-deterministic. We show that this basic opportunistic replacement problem is NP-hard. We show that the convex hull of the set of feasible replacement schedules is full-dimensional, and that all the necessary inequalities also are facet-inducing. We show that when maintenance occasions are fixed, the remaining problem can be stated as a linear program; when maintenance costs are monotone with time, the latter is solvable through a greedy procedure. Results from a series of case studies performed in the areas of aircraft engine and wind turbine maintenance are also reported. These illustrate the advantages of utilizing opportunistic maintenance activities based on a complete optimization model, as compared to simpler policies.
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| 3. |
- Besnard, Francois, 1983, et al.
(författare)
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A stochastic model for opportunistic maintenance planning of offshore wind farms
- 2011
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Ingår i: 2011 IEEE PES Trondheim PowerTech: The Power of Technology for a Sustainable Society, POWERTECH 2011; Trondheim; 19 June 2011 through 23 June 2011. - 9781424484195
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Konferensbidrag (refereegranskat)abstract
- A sound maintenance planning is of crucial importance for wind power farms, and especially for offshore locations. This paper presents a stochastic optimization model for opportunistic service maintenance of offshore wind farms. The model takes advantage of 7 days wind production ensemble forecast and opportunities at corrective maintenance activities in order to perform the service maintenance tasks at the lowest cost. The model is based on a rolling horizon, i.e. the optimization is performed on a daily basis to update the maintenance planning based on the updated production and weather forecasts. An example based on real wind data is used to demonstrate the value of the proposed approach. In this example, it is shown that 32% of the cost for production losses and transportation could be saved. © 2011 IEEE.
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| 4. |
- Gollowitzer, Stefan, et al.
(författare)
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New Models for and Numerical Tests of the Hamiltonian p-Median Problem
- 2011
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642215261 ; 6701/2011, s. 385-394
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Konferensbidrag (refereegranskat)abstract
- The Hamiltonian p-median problem (HpMP) was introduced by [Branco90]. It is closely related to two well-known problems, namely the Travelling Salesman problem (TSP) and the Vehicle Routing problem (VRP). The HpMP is to find exactly p node-disjoint cycles of minimum edge cost, such that each node of the graph is contained in exactly one cycle. We present three new models for the HpMP problem which differ with regard to the constraints that enforce a maximum number of cycles. We demonstrate that one of the models (SEC) is dominated by another model (PCON) with regard to the LP relaxation. Further, we introduce a class of symmetry breaking constraints. We present results regarding the quality of the lower bounds provided by the respective LP relaxations for two of the models, and provide computational results that demonstrate the computational efficiency.
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| 5. |
- Patriksson, Michael, 1964, et al.
(författare)
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The opportunistic replacement problem with individual component lives
- 2011
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We consider an extension of the opportunistic replacement problem, which has been studied by Dickman, Epstein and Wilamowsky [3], Andréasson [2], and Andréasson et al. [1], that allows the individuals of the same component to have nonidentical lives. Formulating and solving this problem defines a first step towards solving the opportunistic replacement problems with uncertain component lives. We show that the problem is NP-hard even with time independent costs, and present two mixed integer linear programming models for the problem. We show that in model I the binary requirement on the majority of the variables can be relaxed; this is in contrast to model II and Andréasson’s [2] model. We remove all superfluous variables and constraints in model I and show that the remaining constraints are facet inducing. We also utilize a linear transformation of model I to obtain a stronger version of model II, model II+, that inherits the polyhedral properties of model I. Numerical experiments show that the solution time of model I is significantly lower than the solution times of both model II and Andréasson’s model. It is also somewhat lower than the solution time of model II+.
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| 6. |
- Patriksson, Michael, 1964, et al.
(författare)
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The stochastic opportunistic replacement problem: A two-stage solution approach
- 2011
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In Almgren et al. 2009 we studied the opportunistic replacement problem, which is a multicomponent maintenance scheduling problem with deterministic component lives. The assumption of deterministic lives is a strong simplification, but valid in applications where critical components are assigned a technical life after which replacement is enforced. Here, we study the stochastic opportunistic replacement problem, which is a more general setting in which component lives are allowed to be stochastic. We consider a stochastic programming approach for the minimization of the expected cost over the remaining planning horizon. Further, we present a means to compute lower bounds on the recourse function. The lower bounds are used in the construction of a decomposition method which extends the integer L-shaped method to incorporate stronger optimality cuts. In order to obtain a computationally tractable model, a two-stage sample average approximation scheme is utilized. Numerical experiments on problem instances from the wind power and aviation industry as well as on two test instances are performed. The results show that the decomposition method is faster than solving the deterministic equivalent on the three more complex instances out of the four instances considered. Furthermore, the numerical experiments show that decisions based on the stochastic programming approach yield a lower average total maintenance cost compared to that of decisions based on simpler maintenance.
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