in multiobjective optimization problems where the costs(functions) are modeled by vectors, such that each dimension of the cost represents a distinct non-commensurate optimization criterion.
These methods allow us to merge objective functions into one function, which allow us to transform a multiobjective optimization problem into a mono-objective optimization problem with additional constraints.
The complexity of multiobjective optimization makes the construction of the performance function a difficult task as it can be constructed [1].
[1]
Multi-objetive Optimization Principles and Case Studies ,Yann Collette . Patrick Siarry ,ISBN 978-3-642-07283-3 ISBN 978-3-662-08883-8 (eBook) DOI 10.1007/978-3-662-08883-8
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