Abstract This paper introduces a multi-objective variant of the marine predators algorithm (MPA) called improved (MOIMPA), which incorporates concepts from Quantum theory. By leveraging theory, MOIMPA aims to enhance MPA’s ability balance between exploration and exploitation find optimal solutions. The utilizes concept inspired by Schrödinger wave function determine position particles in search...

This paper presents a new method for multiobjective optimisation based on gradient projection and local region search. The gradient projection is conducted through the identi®cation of normal vectors of an ecient frontier. The projection of the gradient of a nonlinear utility function onto the tangent plane of the ecient frontier at a given ef®cient solution leads to the de®nition of a feasib...

The quality of solution sets generated by decomposition-based evolutionary multiobjective optimisation (EMO) algorithms depends heavily on the consistency between a given problem’s Pareto front shape and the specified weights’ distribution. A set of weights distributed uniformly in a simplex often lead to a set of well-distributed solutions on a Pareto front with a simplex-like shape, but may f...

We demonstrate the applicability of a new PAINT method to speed up iterations of interactive methods in multiobjective optimization. As our test case, we solve a computationally expensive non-linear, five-objective problem of designing and operating a wastewater treatment plant. The PAINT method interpolates between a given set of Pareto optimal outcomes and constructs a computationally inexpen...

Topology optimization (TO), which is a design technique that does not require parameters, has been attracting attention. TO high degree of freedom and can obtain novel shape suitable for desired purposes. However, the characteristics obtained may be greatly damaged due to uncertainty such as variations in material properties. Also, when multi-objective considered, an increase calculation load b...

A new approach for robust H∞ filtering for a class of Lipschitz nonlinear systems with time-varying uncertainties both in the linear and nonlinear parts of the system is proposed in an LMI framework. The admissible Lipschitz constant of the system and the disturbance attenuation level are maximized simultaneously through convex multiobjective optimization. The resulting H∞ filter guarantees asy...

The productivity of real-world systems is often limited by so-called bottlenecks. Hence, usually companies are not only interested in finding the best ways to schedule their current resources so that their benefits are maximized (optimization), but, in order to increase the productivity, they also conduct some analysis to find bottlenecks in their system and eliminate them in the most efficient...

A method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem...

We give an overview of interactive methods developed for solving nonlinear multiobjective optimization problems. In interactive methods, a decision maker plays an important part and the idea is to support her/him in the search for the most preferred solution. In interactive methods, steps of an iterative solution algorithm are repeated and the decision maker progressively provides preference in...

Real-life engineering optimization problems need Multiobjective Optimization (MOO) tools. These problems are highly nonlinear. As the process of Multiple Criteria Decision-Making (MCDM) is much expanded most MOO problems in different disciplines can be classified on the basis of it. Thus MCDM methods have gained wide popularity in different sciences and applications. Meanwhile the increasing nu...