| 1. |
- Aronsson, Martin, et al.
(författare)
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MILP formulations of cumulative constraints for railway scheduling - A comparative study
- 2009. - 13
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Ingår i: The Proceedings of the 9th Workshop on Algorithmic Methods and Models for Optimization of Railways (ATMOS). - : Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany.
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Konferensbidrag (refereegranskat)abstract
- This paper introduces two Mixed Integer Linear Programming (MILP) models for railway traffic planning using a cumulative scheduling constraint and associated pre-processing filters. We compare standard solver performance for these models on three sets of problems from the railway domain and for two of them, where tasks have unitary resource consumption, we also compare them with two more conventional models. In the experiments, the solver performance of one of the cumulative models is clearly the best and is also shown to scale very well for a large scale practical railway scheduling problem.
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| 2. |
- Aronsson, Martin, et al.
(författare)
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Mixed integer-linear formulations of cumulative scheduling constraints - A comparative study
- 2007. - 1
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper introduces two MILP models for the cumulative scheduling constraint and associated pre-processing filters. We compare standard solver performance for these models on three sets of problems and for two of them, where tasks have unitary resource consumption, we also compare them with two models based on a geometric placement constraint. In the experiments, the solver performance of one of the cumulative models, is clearly the best and is also shown to scale very well for a large scale industrial transportation scheduling problem.
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| 3. |
- Bohlin, Markus
(författare)
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A Local Search System for Solving Constraint Problems of Declarative Graph-Based Global Constraints
- 2005. - 1
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Ingår i: Applications of Declarative Programming and Knowledge Management: 15th International Conference on Applications of Declarative Programming and Knowledge Management, INAP 2004, and 18th Workshop on Logic Programming: Revised Selected Papers. - Berlin, Heidelberg : Springer. - 3540255605 ; , s. 166-184
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a local search constraint solver in which constraints are expressed using cost functions on graph structures of filter constraints of equal type. A similar theoretical approach has previously been used to model a large number of complex global constraints, which motivates the use of such a model in practice. In a local search context, we view global constraints as complex cost functions, encapsulating the structure of the constraints using a graph of variables, values and filter constraints. This representation gives us a declarative model, which can also be used to efficiently compute a cost as well as conflict levels of the variables in the constraints. We have implemented these ideas in a compositional C++ framework called Composer, which can be used to solve systems of graph-based constraints. We demonstrate the usability of this approach on several well-known global constraints, and show by experimental results on two problems that an approach using a graph basis for global constraint modeling is not only possible in practice, but also competitive with existing constraint-based local search systems.
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| 4. |
- Bohlin, Markus, 1976-
(författare)
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A Study of Combinatorial Optimization Problems in Industrial Computer Systems
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A combinatorial optimization problem is an optimization problem where the number of possible solutions are finite and grow combinatorially with the problem size. Combinatorial problems exist everywhere in industrial systems. This thesis focuses on solving three such problems which arise within two different areas where industrial computer systems are often used. Within embedded systems and real-time systems, we investigate the problems of allocating stack memory for an system where a shared stacks may be used, and of estimating the highest response time of a task in a system of industrial complexity. We propose a number of different algorithms to compute safe upper bounds on run-time stack usage whenever the system supports stack sharing. The algorithms have in common that they can exploit commonly-available information regarding timing behaviour of the tasks in the system. Given upper bounds on the individual stack usage of the tasks, it is possible to estimate the worst-case stack behaviour by analysing the possible and impossible preemption patterns. Using relations on offset and precedences, we form a preemption graph, which is further analysed to find safe upper-bounds on the maximal preemptions chain in the system. For the special case where all tasks exist in a single static schedule and share a single stack, we propose a polynomial algorithm to solve the problem. For generalizations of this problem, we propose an exact branch-and-bound algorithm for smaller problems and a polynomial heuristic algorithm for cases where the branch-and-bound algorithm fails to find a solution in reasonable time. All algorithms are evaluated in comprehensive experimental studies. The polynomial algorithm is implemented and shipped in the developer tool set for a commercial real-time operating system, Rubus OS. The second problem we study in the thesis is how to estimate the highest response time of a specified task in a complex industrial real-time system. The response-time analysis is done using a best-effort approach, where a detailed model of the system is simulated on input constructed using a local search procedure. In an evaluation on three different systems we can see that the new algorithm were able to produce higher response times much faster than what has previously been possible. Since the analysis is based on simulation and measurement, the results are not safe in the sense that they are always higher or equal to the true response time of the system. The value of the method lies instead in that it makes it possible to analyse complex industrial systems which cannot be analysed accurately using existing safe approaches. The third problem is in the area of maintenance planning, and focus on how to dynamically plan maintenance for industrial systems. Within this area we have focused on industrial gas turbines and rail vehicles. We have developed algorithms and a planning tool which can be used to plan maintenance for gas turbines and other stationary machinery. In such problems, it is often the case that performing several maintenance actions at the same time is beneficial, since many of these jobs can be done in parallel, which reduces the total downtime of the unit. The core of the problem is therefore how to (or how not to) group maintenance activities so that a composite cost due to spare parts, labor and loss of production due to downtime is minimized. We allow each machine to have individual schedules for each component in the system. For rail vehicles, we have evaluated the effect of replanning maintenance in the case where the component maintenance deadline is set to reflect a maximum risk of breakdown in a Gaussian failure distribution. In such a model, we show by simulation that replanning of maintenance can reduce the number of maintenance stops when the variance and expected value of the distribution are increased. For the gas turbine maintenance planning problem, we have evaluated the planning software on a real-world scenario from the oil and gas industry and compared it to the solutions obtained from a commercial integer programming solver. It is estimated that the availability increase from using our planning software is between 0.5 to 1.0 %, which is substantial considering that availability is currently already at 97-98 %.
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| 5. |
- Bohlin, Markus, et al.
(författare)
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A Tool for Gas Turbine Maintenance Scheduling
- 2009. - 20
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Ingår i: Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence (IAAI'09). - : IEEE Computer Society. - 9781577354239
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Konferensbidrag (refereegranskat)abstract
- We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines. The tool is used to plan the maintenance for turbines manufactured and maintained by Siemens Industrial Turbomachinery AB (SIT AB) with the goal to reduce the direct maintenance costs and the often very costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that feasibility in it is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes, and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using mixed integer linear programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, using our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days with 12%. Compared to a mixed integer programming approach, our algorithm not optimal, but is orders of magnitude faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.
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| 6. |
- Bohlin, Markus, et al.
(författare)
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Ansatser för flexibel planering och schemaläggning av tågtidtabeller
- 2006. - 1
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Rapporten beskriver möjliga ansatser för att lösa det abstraherade tidtabellproblemet som bl.a. diskuteras i rapporten "Leveranstågplan: Specifikation och åtagande" (DDTP Arbetsdokument SICS-DDTP-002). Till grund för de olika ansatserna ligger en modell med avgångstider och hålltider (dvs. väntetider och i viss mån traverseringstider) som tillåts variera inom vissa tidsintervall. Huvudidén är att arbeta med förenklade kapacitetsvillkor på bana och bangård, för att på ett effektivt sätt kunna beräkna tidtabeller på en nivå som tillåter anpassning av tidtabellen till det gällande transportbehovet och den rådande trafiksituationen.
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| 7. |
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| 8. |
- Bohlin, Markus, et al.
(författare)
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Bounding Shared-Stack Usage in Systems with Offsets and Precedences
- 2008
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Ingår i: ECRTS 2008: PROCEEDINGS OF THE 20TH EUROMICRO CONFERENCE ON REAL-TIME SYSTEMS. - 9780769532981 ; , s. 276-285
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Konferensbidrag (refereegranskat)abstract
- The paper presents two novel methods to bound the stack memory used in preemptive, shared stack, real-time systems. The first method is based on branch-and-bound search for possible preemption patterns, and the second one approximates the first in polynomial time. The work extends previous methods by considering a more general task-model, in which all tasks can share the same stack. In addition, the new methods account for precedence and offset relations. Thus, the methods give tight bounds for a large set of realistic systems. The methods have been implemented and a comprehensive evaluation, comparing our new methods against each other and against existing methods, is presented. The evaluation shows that our exact method can significantly reduce the amount of stack memory needed.
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| 9. |
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| 10. |
- Bohlin, Markus, et al.
(författare)
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Optimization of condition-based maintenance for industrial gas turbines: Requirements and results
- 2009
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Ingår i: Proceedings of the ASME Turbo Expo Volume 5. - 9780791848869 ; , s. 455-464
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Konferensbidrag (refereegranskat)abstract
- In oil and gas applications, the careful planning and execution of preventive maintenance is important due to the high costs associated with shutdown of critical equipment. Optimization and lifetime management for equipment such as gas turbines is therefore crucial in order to achieve high availability and reliability. In this paper, a novel condition-based gas turbine maintenance strategy is described and evaluated. Using custom-madegas turbine maintenance planning software, maintenance is repeatedly reoptimized to fit into the time intervals where production losses are least costly and result in the lowest possible impact. The strategy focuses on accurate online lifetime estimates for gas turbine components, where algorithms predicting future maintenance requirements are used to produce maintenance deadlines. This ensures that the gas turbines are maintained in accordance with the conditions on site. To show the feasibility and economic effects of a customer-adapted maintenance planning process, the maintenance plan for a gas turbine used in a real-world scenario is optimized using a combinatorial optimization algorithm and input from gas turbine operation data, maintenance schedules and operator requirements. The approach was validated through the inspection of a reference gas turbine after a predetermined time interval. It is shown that savings may be substantial compared to a traditional preventivemaintenance plan. In the evaluation, typical cost reductions range from 25 to 65 %. The calculated availability increase in practice is estimated to range from 0.5 to 1 %. In addition, down-time reductions of approximately 12 % are expected, due solely to improved planning. This indicates significant improvements.
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