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Grimm, Henrik
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Publikasjoner (10 av 24) Visa alla publikasjoner
Syberfeldt, A., Grimm, H., Ng, A. & John, R. I. (2008). A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems. In: 2008 IEEE Congress on Evolutionary Computation, CEC 2008: . Paper presented at 2008 IEEE Congress on Evolutionary Computation, CEC 2008; Hong Kong; 1 June 2008 through 6 June 2008; Category number 08TH8988; Code 73863 (pp. 3177-3184). IEEE conference proceedings
Åpne denne publikasjonen i ny fane eller vindu >>A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
2008 (engelsk)Inngår i: 2008 IEEE Congress on Evolutionary Computation, CEC 2008, IEEE conference proceedings, 2008, s. 3177-3184Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2008
Serie
IEEE Congress on Evolutionary Computation
Emneord
Algorithm design and analysis, Benchmark testing, Concurrent computing, Evolutionary computation, Filters, Manufacturing, Optimization methods, Parallel processing, Steady-state, Uncertainty
HSV kategori
Identifikatorer
urn:nbn:se:his:diva-7128 (URN)10.1109/CEC.2008.4631228 (DOI)000263406502002 ()2-s2.0-55749108832 (Scopus ID)978-1-4244-1823-7 (ISBN)978-1-4244-1822-0 (ISBN)
Konferanse
2008 IEEE Congress on Evolutionary Computation, CEC 2008; Hong Kong; 1 June 2008 through 6 June 2008; Category number 08TH8988; Code 73863
Tilgjengelig fra: 2013-02-06 Laget: 2013-02-06 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Syberfeldt, A., Grimm, H. & Ng, A. (2008). Design of Experiments for Training Metamodels in Simulation-Based Optimisation of Manufacturing Systems. In: Proceedings of The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08): . Paper presented at The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08)Skövde, Sweden, June 30-July 2, 2008. Skövde: University of Skövde
Åpne denne publikasjonen i ny fane eller vindu >>Design of Experiments for Training Metamodels in Simulation-Based Optimisation of Manufacturing Systems
2008 (engelsk)Inngår i: Proceedings of The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08), Skövde: University of Skövde , 2008Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Skövde: University of Skövde, 2008
HSV kategori
Identifikatorer
urn:nbn:se:his:diva-7331 (URN)978-91-633-2757-5 (ISBN)
Konferanse
The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08)Skövde, Sweden, June 30-July 2, 2008
Tilgjengelig fra: 2013-02-26 Laget: 2013-02-26 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Syberfeldt, A., Grimm, H., Ng, A. & Moore, P. (2008). Multi-Objective Evolutionary Simulation-Optimization of a Real-World Manufacturing Problem. In: Proceedings of The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08): . Paper presented at The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08), Skövde, Sweden, June 30-July 2, 2008.. Skövde: University of Skövde
Åpne denne publikasjonen i ny fane eller vindu >>Multi-Objective Evolutionary Simulation-Optimization of a Real-World Manufacturing Problem
2008 (engelsk)Inngår i: Proceedings of The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08), Skövde: University of Skövde , 2008Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Skövde: University of Skövde, 2008
HSV kategori
Identifikatorer
urn:nbn:se:his:diva-7332 (URN)978-91-633-2757-5 (ISBN)
Konferanse
The 18th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM'08), Skövde, Sweden, June 30-July 2, 2008.
Tilgjengelig fra: 2013-02-26 Laget: 2013-02-26 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Ng, A., Syberfeldt, A., Grimm, H. & Svensson, J. (2008). Multi-Objective Simulation Optimization and Significant Dominance for Comparing Production Control Mechanisms. In: Proceedings of the 18th International Conference on Flexible Automation and Intelligent Manufacturing, Skövde, Sweden, 2008: . Paper presented at The 18th International Conference on Flexible Automation and Intelligent Manufacturing, Skövde, Sweden, 2008. Skövde: University of Skövde
Åpne denne publikasjonen i ny fane eller vindu >>Multi-Objective Simulation Optimization and Significant Dominance for Comparing Production Control Mechanisms
2008 (engelsk)Inngår i: Proceedings of the 18th International Conference on Flexible Automation and Intelligent Manufacturing, Skövde, Sweden, 2008, Skövde: University of Skövde , 2008Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Skövde: University of Skövde, 2008
HSV kategori
Identifikatorer
urn:nbn:se:his:diva-7328 (URN)978-91-633-2757-5 (ISBN)
Konferanse
The 18th International Conference on Flexible Automation and Intelligent Manufacturing, Skövde, Sweden, 2008
Tilgjengelig fra: 2013-02-26 Laget: 2013-02-26 Sist oppdatert: 2018-05-14bibliografisk kontrollert
Syberfeldt, A., Grimm, H. & Ng, A. (2008). Multi-Objective Simulation-Based Optimization of Production Systems with Consideration Noise. In: Bengt Åke Lindberg & Johan Stahre (Ed.), : . Paper presented at 2nd Swedish Production Symposium (SPS) 2008, Stockholm, Sweden, November 18-20, 2008. Stockholm: Swedish Production Academy
Åpne denne publikasjonen i ny fane eller vindu >>Multi-Objective Simulation-Based Optimization of Production Systems with Consideration Noise
2008 (engelsk)Inngår i: / [ed] Bengt Åke Lindberg & Johan Stahre, Stockholm: Swedish Production Academy , 2008Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Many production optimization problems approached by simulation are subject to noise.When evolutionary algorithms are applied to such problems, noise during evaluation of solutions adversely affects the evolutionary selection process and the performance of the algorithm. In this paper we present a noise compensation technique that efficiently deals with the negative effects of noisy simulations in multi-objective optimization problems. Basically, this technique uses an iterative re-sampling procedure that reduces the noise until the likelihood of selecting the correct solution reaches a given confidence level. The technique is implemented in MOPSA-EA, an existing evolutionary algorithm designed specifically for real-world simulation-optimization problems. In evaluating the new technique, it is applied on a benchmark problem and on two real-world problems of manufacturing optimization. A comparison of the performance of existing algorithms indicates the potential of the proposed technique.

sted, utgiver, år, opplag, sider
Stockholm: Swedish Production Academy, 2008
Emneord
simulation, optimization, noise
Identifikatorer
urn:nbn:se:his:diva-7181 (URN)
Konferanse
2nd Swedish Production Symposium (SPS) 2008, Stockholm, Sweden, November 18-20, 2008
Tilgjengelig fra: 2013-02-08 Laget: 2013-02-08 Sist oppdatert: 2017-11-27
Ng, A., Grimm, H., Lezama, T., Persson, A., Andersson, M. & Jägstam, M. (2008). OPTIMISE: An Internet-Based Platform for Metamodel-Assisted Simulation Optimization. In: Xu Huang, Yuh-Shyan Chen, Sio-Iong Ao (Ed.), Advances in Communication Systems and Electrical Engineering: (pp. 281-296). Springer Science+Business Media B.V.
Åpne denne publikasjonen i ny fane eller vindu >>OPTIMISE: An Internet-Based Platform for Metamodel-Assisted Simulation Optimization
Vise andre…
2008 (engelsk)Inngår i: Advances in Communication Systems and Electrical Engineering / [ed] Xu Huang, Yuh-Shyan Chen, Sio-Iong Ao, Springer Science+Business Media B.V., 2008, s. 281-296Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Computer simulation has been described as the most effective tool for de-signing and analyzing systems in general and discrete-event systems (e.g., production or logistic systems) in particular (De Vin et al. 2004). Historically, the main disadvantage of simulation is that it was not a real optimization tool. Recently, research efforts have been focused on integrating metaheuristic algorithms, such as genetic algorithms (GA) with simulation software so that “optimal” or close to optimal solutions can be found automatically. An optimal solution here means the setting of a set of controllable design variables (also known as decision variables) that can minimize or maximize an objective function. This approach is called simulation optimization or simulation-based optimization (SBO), which is perhaps the most important new simulation technology in the last few years (Law and McComas 2002). In contrast to other optimization problems, it is assumed that the objective function in an SBO problem cannot be evaluated analytically but have to be estimated through deterministic/ stochastic simulation.

sted, utgiver, år, opplag, sider
Springer Science+Business Media B.V., 2008
Serie
Lecture Notes in Electrical Engineering, ISSN 1876-1100 ; 4
HSV kategori
Identifikatorer
urn:nbn:se:his:diva-2801 (URN)10.1007/978-0-387-74938-9_20 (DOI)2-s2.0-84885011189 (Scopus ID)978-0-387-74937-2 (ISBN)978-0-387-74938-9 (ISBN)
Tilgjengelig fra: 2009-03-02 Laget: 2009-03-02 Sist oppdatert: 2018-01-13bibliografisk kontrollert
Andersson, M., Ng, A. & Grimm, H. (2008). Simulation Optimization for Industrial Scheduling Using Hybrid Genetic Representation. In: S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler (Ed.), Proceedings of the 2008 Winter Simulation Conference: . Paper presented at 2008 Winter Simulation Conference, WSC 2008, Miami, FL, United States, 7 December 2008 through 10 December 2008 (pp. 2004-2011). IEEE conference proceedings
Åpne denne publikasjonen i ny fane eller vindu >>Simulation Optimization for Industrial Scheduling Using Hybrid Genetic Representation
2008 (engelsk)Inngår i: Proceedings of the 2008 Winter Simulation Conference / [ed] S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler, IEEE conference proceedings, 2008, s. 2004-2011Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Simulation modeling has the capability to represent complex real-world systems in details and therefore it is suitable to develop simulation models for generating detailed operation plans to control the shop floor. In the literature, there are two major approaches for tackling the simulation-based scheduling problems, namely dispatching rules and using meta-heuristic search algorithms. The purpose of this paper is to illustrate that there are advantages when these two approaches are combined. More precisely, this paper introduces a novel hybrid genetic representation as a combination of both a partially completed schedule (direct) and the optimal dispatching rules (indirect), for setting the schedules for some critical stages (e.g. bottlenecks) and other non-critical stages respectively. When applied to an industrial case study, this hybrid method has been found to outperform the two common approaches, in terms of finding reasonably good solutions within a shorter time period for most of the complex scheduling scenarios.

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2008
Forskningsprogram
Teknik
Identifikatorer
urn:nbn:se:his:diva-2865 (URN)000274496201031 ()2-s2.0-60749101234 (Scopus ID)978-1-4244-2708-6 (ISBN)
Konferanse
2008 Winter Simulation Conference, WSC 2008, Miami, FL, United States, 7 December 2008 through 10 December 2008
Tilgjengelig fra: 2009-03-17 Laget: 2009-03-17 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Syberfeldt, A., Grimm, H., Ng, A., Andersson, M. & Karlsson, I. (2008). Simulation-Based Optimization of a Complex Mail Transportation Network. In: S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler (Ed.), Proceedings of the 2008 Winter Simulation Conference: . Paper presented at 2008 Winter Simulation Conference, WSC 2008; Miami, FL; 7 December 2008 through 10 December 2008; Category number 08CH38051; Code75374 (pp. 2625-2631). New York: IEEE conference proceedings
Åpne denne publikasjonen i ny fane eller vindu >>Simulation-Based Optimization of a Complex Mail Transportation Network
Vise andre…
2008 (engelsk)Inngår i: Proceedings of the 2008 Winter Simulation Conference / [ed] S. J. Mason, R. R. Hill, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler, New York: IEEE conference proceedings, 2008, s. 2625-2631Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Swedish Postal Services receives and distributes over 22 million pieces of mail every day. Mail transportation takes place overnight by airplanes, trains, trucks, and cars in a transportation network comprising a huge number of possible routes. For testing and analysis of different transport solutions, a discrete-event simulation model of the transportation network has been developed. This paper describes the optimization of transport solutions using evolutionary algorithms coupled with the simulation model. The vast transportation network in combination with a large number of possible transportation configurations and conflicting optimization criteria make the optimization problem very challenging. A large number of simulation evaluations are needed before an acceptable solution is found, making the computational cost of the problem severe. To address this problem, a computationally cheap surrogate model is used to offload the optimization process.

sted, utgiver, år, opplag, sider
New York: IEEE conference proceedings, 2008
Forskningsprogram
Teknik
Identifikatorer
urn:nbn:se:his:diva-2866 (URN)10.1109/WSC.2008.4736377 (DOI)000274496201113 ()2-s2.0-60749125483 (Scopus ID)978-1-4244-2708-6 (ISBN)
Konferanse
2008 Winter Simulation Conference, WSC 2008; Miami, FL; 7 December 2008 through 10 December 2008; Category number 08CH38051; Code75374
Tilgjengelig fra: 2009-03-17 Laget: 2009-03-17 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Persson, A., Grimm, H., Ng, A. & Jägstam, M. (2007). A Case Study of Using Simulation and Soft Computing Techniques for Optimisation of Manufacturing Systems. In: Proceedings of Swedish Production Symposium 2007, Gothenburg, Sweden, August 28-30, 2007: . Paper presented at Swedish Production Symposium 2007, Gothenburg, Sweden, August 28-30, 2007.
Åpne denne publikasjonen i ny fane eller vindu >>A Case Study of Using Simulation and Soft Computing Techniques for Optimisation of Manufacturing Systems
2007 (engelsk)Inngår i: Proceedings of Swedish Production Symposium 2007, Gothenburg, Sweden, August 28-30, 2007, 2007Konferansepaper, Publicerat paper (Fagfellevurdert)
Identifikatorer
urn:nbn:se:his:diva-7327 (URN)
Konferanse
Swedish Production Symposium 2007, Gothenburg, Sweden, August 28-30, 2007
Tilgjengelig fra: 2013-02-26 Laget: 2013-02-26 Sist oppdatert: 2017-11-27bibliografisk kontrollert
Persson, A., Grimm, H. & Ng, A. (2007). A Metamodel-Assisted Steady-State Evolution Strategy for Simulation-Based Optimization. In: Oscar Castillo, Li Xu, Sio-Iong Ao (Ed.), Trends in Intelligent Systems and Computer Engineering: (pp. 1-13). Springer Science+Business Media B.V.
Åpne denne publikasjonen i ny fane eller vindu >>A Metamodel-Assisted Steady-State Evolution Strategy for Simulation-Based Optimization
2007 (engelsk)Inngår i: Trends in Intelligent Systems and Computer Engineering / [ed] Oscar Castillo, Li Xu, Sio-Iong Ao, Springer Science+Business Media B.V., 2007, s. 1-13Kapittel i bok, del av antologi (Fagfellevurdert)
sted, utgiver, år, opplag, sider
Springer Science+Business Media B.V., 2007
Serie
Lecture Notes in Electrical Engineering, ISSN 1876-1100 ; 6
Identifikatorer
urn:nbn:se:his:diva-7296 (URN)10.1007/978-0-387-74935-8_1 (DOI)2-s2.0-78651536859 (Scopus ID)978-0-387-74935-8 (ISBN)978-0-387-74934-1 (ISBN)
Tilgjengelig fra: 2013-02-25 Laget: 2013-02-25 Sist oppdatert: 2017-11-27bibliografisk kontrollert
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