THESIS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Product Configuration from a Mathematical Optimization Perspective

The optimal truck configuration for a certain customer is very specific and depends on for what transport mission and in which operating environment the truck is to be used. In addition, the customers normally specify other feature requirements ranging from visual appearance to advanced driver support systems. For this reason, the truck configurations that are made available for the customers are highly specialized. To achieve this in a cost efficient way, the manufacturer must be able to produce these configurations with a limited set of technical solutions. This is done by the use of a common architecture, in which technology is shared such that the same parts are used in different combinations, leading to a relatively small number of parts but a large number of possible configurations. This thesis presents an approach to the configuration problem by analyzing it from a mathematical optimization perspective. By assuming that a truck can be described by a number of quality measures, which different customers may appreciate differently, the problem of deciding on a good product offer can naturally be formulated within a multi-objective optimization framework. The areas within product development in which mathematical optimization can be applied are many and most often fundamentally different. In this thesis several subproblems of the whole product development problem are formulated in mathematical terms, and in the appended papers, the resulting mathematical models are considered in generalized forms. As established in the different papers, not just one optimization discipline is relevant in the product development context. The disciplines considered include multi-objective optimization, clustering, robust optimization, continuous global optimization, and nonlinear integer programming with an extension to a special type of non-sortable discrete variables.