Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/309517 
Year of Publication: 
2023
Citation: 
[Journal:] Mathematical Methods of Operations Research [ISSN:] 1432-5217 [Volume:] 100 [Issue:] 1 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2023 [Pages:] 385-410
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Application problems can often not be solved adequately by numerical algorithms as several difficulties might arise at the same time. When developing and improving algorithms which hopefully allow to handle those difficulties in the future, good test instances are required. These can then be used to detect the strengths and weaknesses of different algorithmic approaches. In this paper we present a generator for test instances to evaluate solvers for multiobjective mixed-integer linear and nonlinear optimization problems. Based on test instances for purely continuous and purely integer problems with known efficient solutions and known nondominated points, suitable multiobjective mixed-integer test instances can be generated. The special structure allows to construct instances scalable in the number of variables and objective functions. Moreover, it allows to control the resulting efficient and nondominated sets as well as the number of efficient integer assignments.
Subjects: 
Multiobjective optimization
Mixed-integer optimization
Test instances
Nonconvex optimization
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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