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Models and Methods for Costly Global Optimization and Military Decision Support SystemsPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
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PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2012 (English)Doctoral thesis, comprehensive summary (Other academic)
##### Abstract [en]

##### Place, publisher, year, edition, pages

Linköping: Linköping University Electronic Press, 2012. , 39 p.
##### Series

Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1450
##### National Category

Computational Mathematics
##### Identifiers

URN: urn:nbn:se:liu:diva-77078ISBN: 978-91-7519-891-0OAI: oai:DiVA.org:liu-77078DiVA: diva2:524846
##### Public defence

2012-06-04, C3, C-huset, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
##### Opponent

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##### Supervisors

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#####

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Available from: 2012-05-04 Created: 2012-05-04 Last updated: 2015-02-25Bibliographically approved
##### List of papers

The thesis consists of five papers. The first three deal with topics within costly global optimization and the last two concern military decision support systems.

The first part of the thesis addresses so-called costly problems where the objective function is seen as a “black box” to which the input parameter values are sent and a function value is returned. This means in particular that no information about derivatives is available. The black box could, for example, solve a large system of differential equations or carry out timeconsuming simulation, where a single function evaluation can take several hours! This is the reason for describing such problems as costly and why they require customized algorithms. The goal is to construct algorithms that find a (near)-optimal solution using as few function evaluations as possible. A good example of a real life application comes from the automotive industry, where the development of new engines utilizes advanced mathematical models that are governed by a dozen key parameters. The objective is to optimize the engine by changing these parameters in such a way that it becomes as energy efficient as possible, but still meets all sorts of demands on strength and external constraints. The first three papers describe algorithms and implementation details for these costly global optimization problems.

The second part deals with military mission planning, that is, problems that concern logistics, allocation and deployment of military resources. Given a fleet of resource, the decision problem is to allocate the resources against the enemy so that the overall mission success is optimized. We focus on the problem of the attacker and consider two separate problem classes. In the fourth paper we introduce an effect oriented planning approach to an advanced weapon-target allocation problem, where the objective is to maximize the expected outcome of a coordinated attack. We present a mathematical model together with efficient solution techniques. Finally, in the fifth paper, we introduce a military aircraft mission planning problem, where an aircraft fleet should attack a given set of targets. Aircraft routing is an essential part of the problem, and the objective is to maximize the expected mission success while minimizing the overall mission time. The problem is stated as a generalized vehicle routing model with synchronization and precedence side constraints.

1. An adaptive radial basis algorithm (ARBF) for expensive black-box mixed-integer constrained global optimization$(function(){PrimeFaces.cw("OverlayPanel","overlay524839",{id:"formSmash:j_idt423:0:j_idt427",widgetVar:"overlay524839",target:"formSmash:j_idt423:0:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

2. The Influence of Experimental Designs on the performance of surrogate model based costly global optimization solvers$(function(){PrimeFaces.cw("OverlayPanel","overlay524841",{id:"formSmash:j_idt423:1:j_idt427",widgetVar:"overlay524841",target:"formSmash:j_idt423:1:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

3. Implementation of a One-Stage Efficient Global Optimization (EGO) Algorithm$(function(){PrimeFaces.cw("OverlayPanel","overlay524834",{id:"formSmash:j_idt423:2:j_idt427",widgetVar:"overlay524834",target:"formSmash:j_idt423:2:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

4. Effect Oriented Planning$(function(){PrimeFaces.cw("OverlayPanel","overlay524831",{id:"formSmash:j_idt423:3:j_idt427",widgetVar:"overlay524831",target:"formSmash:j_idt423:3:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

5. Aircraft Mission Planning$(function(){PrimeFaces.cw("OverlayPanel","overlay524832",{id:"formSmash:j_idt423:4:j_idt427",widgetVar:"overlay524832",target:"formSmash:j_idt423:4:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

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