Toward an estimation of nadir objective vector using a hybrid of evolutionary and local search approaches

A nadir objective vector is constructed from the worst Pareto-optimal objective values in a multiobjective optimization problem and is an important entity to compute because of its significance in estimating the range of objective values in the Pareto-optimal front and also in executing a number of interactive multiobjective optimization techniques. Along with the ideal objective vector, it is also needed for the purpose of normalizing different objectives, so as to facilitate a comparison and agglomeration of the objectives. However, the task of estimating the nadir objective vector necessitates information about the complete Pareto-optimal front and has been reported to be a difficult task, and importantly an unsolved and open research issue. In this paper, we propose certain modifications to an existing evolutionary multiobjective optimization procedure to focus its search toward the extreme objective values and combine it with a reference-point based local search approach to constitute a couple of hybrid procedures for a reliable estimation of the nadir objective vector. With up to 20-objective optimization test problems and on a three-objective engineering design optimization problem, one of the proposed procedures is found to be capable of finding the nadir objective vector reliably. The study clearly shows the significance of an evolutionary computing based search procedure in assisting to solve an age-old important task in the field of multiobjective optimization

Polymer single screw extruder optimization using tchebycheff scalarization method and simulated annealing algorithm

The single screw extrusion optimal design involves the optimization of six criteria that can be efficiently handled by a weighted Tchebycheff scalarization method. The performance of the method has been analyzed for three different methods to generate weight vectors. The experimental results show that the tested strategies provide similar and reasonable solutions and supply a valuable procedure to identify good trade-offs between conflicting objectives.European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 734205- H2020-MSCA-RISE-2017. The work has also been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, UIDB/00013/2020 and UIDP/00013/2020 of CMAT-U

A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.Evolutionary algorithms are widely used for solving multiobjective optimization problems but are often criticized because of a large number of function evaluations needed. Approximations, especially function approximations, also referred to as surrogates or metamodels are commonly used in the literature to reduce the computation time. This paper presents a survey of 45 different recent algorithms proposed in the literature between 2008 and 2016 to handle computationally expensive multiobjective optimization problems. Several algorithms are discussed based on what kind of an approximation such as problem, function or fitness approximation they use. Most emphasis is given to function approximation-based algorithms. We also compare these algorithms based on different criteria such as metamodeling technique and evolutionary algorithm used, type and dimensions of the problem solved, handling constraints, training time and the type of evolution control. Furthermore, we identify and discuss some promising elements and major issues among algorithms in the literature related to using an approximation and numerical settings used. In addition, we discuss selecting an algorithm to solve a given computationally expensive multiobjective optimization problem based on the dimensions in both objective and decision spaces and the computation budget available.The research of Tinkle Chugh was funded by the COMAS Doctoral Program (at the University of Jyväskylä) and FiDiPro Project DeCoMo (funded by Tekes, the Finnish Funding Agency for Innovation), and the research of Dr. Karthik Sindhya was funded by SIMPRO project funded by Tekes as well as DeCoMo

Technological and design aspects of the processing of composites and nanocomposites. Volume III

Processing of composites and nanocomposites materials constitutes nowadays an important area of research given the growing interest by these types of materials due to its singular properties, namely in what concerns technological and design aspects. This monography presents the developments taking place in the framework of the NEWEX project during the fourth year of its duration, which is a sequence of other two previous monographies. The main objective of the NEWEX project entitled “Investigation and development of a new generation of machines for the processing of composite and nanocomposites materials” is the exchange of researchers from the institutions participating in the project. Another important objective consists in develop permanent international and inter-sector collaboration between academic research centres (Lublin University of Technology, Technical University of Kosice, University of Minho) and industrial organizations (Zamak-Mercator LLC and SEZ-Krompachy a.s., Dirmeta UAB). The contents of this book reflects the work done within the NEWEX project. It starts by presenting the results obtained concerning new concepts for the extruder parts studied and the manufacturing of those extruder parts. Then, some approaches for modelling and optimizing and to study experimentally the process are described, which includes mixing analysis and monitoring. Finally, a practical and state-of-theart application of the extrusion is identified, namely 3D printing. It is expected that the nine chapters of this monography be useful to the industry of plastics processing and for scientific organisations dealing with technologies and processing of polymer composites and nanocomposites