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| 2. |
- Nedelkova, Zuzana, 1987, et al.
(author)
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A splitting algorithm for simulation-based optimization problems with categorical variables
- 2019
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In: Engineering Optimization. - 1029-0273 .- 0305-215X. ; 51:5, s. 815-831
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Journal article (peer-reviewed)abstract
- In the design of complex products, some product components can only be chosen from a finite set of options. Each option then corresponds to a multidimensional point representing the specifications of the chosen components. A splitting algorithm that explores the resulting discrete search space and is suitable for optimization problems with simulation-based objective functions is presented. The splitting rule is based on the representation of a convex relaxation of the search space in terms of a minimum spanning tree and adopts ideas from multilevel coordinate search. The objective function is underestimated on its domain by a convex quadratic function. The main motivation is the aim to find—for a vehicle and environment specification—a configuration of the tyres such that the energy losses caused by them are minimized. Numerical tests on a set of optimization problems are presented to compare the performance of the algorithm developed with that of other existing algorithms.
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| 3. |
- Nedelkova, Zuzana, 1987, et al.
(author)
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Efficient solution of many instances of a simulation-based optimization problem utilizing a partition of the decision space
- 2018
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In: Annals of Operations Research. - : Springer Science and Business Media LLC. - 1572-9338 .- 0254-5330. ; 265:1, s. 93-118
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Journal article (peer-reviewed)abstract
- This paper concerns the solution of a class of mathematical optimization problems with simulation-based objective functions. The decision variables are partitioned into two groups, referred to as variables and parameters, respectively, such that the objective function value is influenced more by the variables than by the parameters. We aim to solve this optimization problem for a large number of parameter settings in a computationally efficient way. The algorithm developed uses surrogate models of the objective function for a selection of parameter settings, for each of which it computes an approximately optimal solution over the domain of the variables. Then, approximate optimal solutions for other parameter settings are computed through a weighting of the surrogate models without requiring additional expensive function evaluations. We have tested the algorithm's performance on a set of global optimization problems differing with respect to both mathematical properties and numbers of variables and parameters. Our results show that it outperforms a standard and often applied approach based on a surrogate model of the objective function over the complete space of variables and parameters.
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| 4. |
- Nedelkova, Zuzana, 1987, et al.
(author)
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Integration of expert knowledge into radial basis function surrogate models
- 2016
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In: Optimization and Engineering. - : Springer Science and Business Media LLC. - 1389-4420 .- 1573-2924. ; 17:3, s. 577-603
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Journal article (peer-reviewed)abstract
- A current application in a collaboration between Chalmers University of Technology and Volvo Group Trucks Technology concerns the global optimization of a complex simulation-based function describing the rolling resistance coefficient of a truck tyre. This function is crucial for the optimization of truck tyres selection considered. The need to explicitly describe and optimize this function provided the main motivation for the research presented in this article. Many optimization algorithms for simulation-based optimization problems use sample points to create a computationally simple surrogate model of the objective function. Typically, not all important characteristics of the complex function (as, e.g., non-negativity)—here referred to as expert knowledge—are automatically inherited by the surrogate model. We demonstrate the integration of several types of expert knowledge into a radial basis function interpolation. The methodology is first illustrated on a simple example function and then applied to a function describing the rolling resistance coefficient of truck tyres. Our numerical results indicate that expert knowledge can be advantageously incorporated and utilized when creating global approximations of unknown functions from sample points.
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| 5. |
- Nedelkova, Zuzana, 1987, et al.
(author)
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Modelling of optimal tyres selection for a certain truck and transport application
- 2017
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In: International Journal of Vehicle Systems Modelling and Testing. - 1745-6444 .- 1745-6436. ; 12:3/4, s. 284-303
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Journal article (peer-reviewed)abstract
- The main aim of the research leading to this paper is to select---for a truck and its transport application---a configuration of the tyres such that the energy losses caused by these are minimized. We show that neither the rolling resistance coefficient (RRC) classes provided by tyre suppliers nor any other nominal values of RRC evaluated for specific operating conditions are sufficient to do the tyres selection. Therefore, a surrogate model of the RRC is developed. A tyre model based on the RRC model is introduced in this paper. The modularity of the tyre model is demonstrated by coupling it with two different vehicle models and an~operating environment model. The usage of the joint vehicle, tyres, and operating environment model is demonstrated by solving a few illustrative instances of the tyres selection problem. The potential savings wrt. energy losses when the selected tyre configurations are used are presented.
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| 6. |
- Nedelkova, Zuzana, 1987
(author)
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Optimization of truck tyres selection
- 2018
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Doctoral thesis (other academic/artistic)abstract
- This thesis, which consists of an introduction and five appended papers, concerns the optimal selection of tyres for a variety of vehicle configurations as well as operating environments. The selection problem stems from a project cooperation between Chalmers University of Technology and Volvo Group Trucks Technology. We analyze the selection problem from a mathematical optimization point of view. The overall purpose is to reduce the tractive energy required to run the vehicle. We develop a computationally efficient vehicle dynamics model of the vehicle, the tyres, and the operating environment. The tyres are represented by a surrogate model of the rolling resistance coefficient, which measures the energy losses caused by the tyres. The properties of the surrogate model called for a methodology for connecting expert knowledge about a general simulation-based function with its radial basis function interpolation. An algorithm for the solution of a large set of instances of a simulation-based optimization problem with continuous variables has been developed and tested on a set of problem instances. This algorithm enables an efficient computation of approximately optimal tyre designs (represented by continuous variables) for each vehicle configuration and operating environment specification. A splitting algorithm for simulation-based optimization problems with categorical variables has been developed and evaluated on a set of test problems. This algorithm outperforms all algorithms applicable to this class of optimization problems, and finds an approximately optimal tyres configuration. Since each execution of this algorithm requires many computationally expensive evaluations of the simulation-based objective function, it cannot be used to solve the full tyres selection problem. The two latter algorithms are then combined to enable the efficient solution of many instances of a simulation-based optimization problem with categorical variables. The resulting algorithm is applied to a couple of instances of the tyres selection problem. Our experiments show that the optimization methodology developed enables a computationally efficient solution of the truck tyres selection problem, in the combinatorial domain of possible vehicle configurations and operating environment specifications. Putting our methodology into practice will involve many challenges besides the problems studied in this thesis; however we have shown that our methodology can be utilized in the sales tool at Volvo.
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| 7. |
- Nedelkova, Zuzana, 1987
(author)
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TyreOpt - Phase I
- 2016
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Reports (other academic/artistic)
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| 8. |
- Odrigo, Arnold, et al.
(author)
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DESIGN AND DEVELOPMENT OF A ROAD PROFILE GENERATOR
- 2016
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In: International Journal of Vehicle Systems Modelling and Testing. - 1745-6436. ; 11:3, s. 217-233
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Journal article (peer-reviewed)abstract
- Ride comfort, fuel consumption and vehicle dynamics are of great importance in vehicle design, development and testing. For this reason, a method of generating a random road profile in three-dimensional space is explored. This is done by combining established mathematical theories of defining road curvature, topography and surface roughness. Though the generated profile is random by nature, its most important aforementioned characteristics are controlled using guidelines and parameters from real roads. Examples of these are the Volvo Global Transport Application (GTA) as well as the International Organization for Standardization (ISO). With the use of MATLAB to develop the program, statistical distributions and probability models are employed for generating the variations in both topography and curviness of the road. Topography is implemented in percent elevation gradients, while clothoid spirals are employed for creating a natural road curvature using tabulated road statistics. Finally, surface roughness will be defined through the use of standardised power spectral density values of ISO roughness classifications. The proposed road generator program creates a road which is independent of the vehicle itself, which is important to compare different vehicles or vehicle designs for same transport task. This is important to create a universally-compatible road profile for several tests. The road profiles will aid in various tests as required throughout the entire automotive industry.
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| 9. |
- Odrigo, Arnold, et al.
(author)
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Design and development of a road profile generator
- 2016
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In: International Journal of Vehicle Systems Modelling and Testing. - 1745-6444 .- 1745-6436. ; 11:3, s. 217-233
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Journal article (peer-reviewed)abstract
- This work aims to develop a method of generating a random road profile in three-dimensional space based on existing road design and classification standards and parameters, such examples being the Volvo Global Transport Application (GTA) and the International Organization of Standards (ISO). This is done by combining probability models, statistical distributions and mathematical methods of defining road curves, elevation and surface roughness through the use of MATLAB code. The proposed road profile generator code creates a road in three-dimensional space independent of vehicle characteristics and behaviour. The ultimate goal of this work is to contribute to the capabilities of modern virtual vehicle simulation systems by incorporating more random environments with respect to a wide range of established national standards to better simulate real driving loads.
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