Nowadays, with extending applications of bi-layer metallic sheets in different industrial sectors, accurate specification of each layer is very prominent to achieve desired properties. In order to predict behavior of sheets under different forming modes and determining rupture limit and necking, the concept of Forming Limit Diagram (FLD) is used. Optimization problem with objective functions an...

In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. The K-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhou...

The problem of simultaneously optimizing the information rate and harvested power in a reconfigurable intelligent surface (RIS)-aided multiple-input single-output downlink multiuser wireless network with simultaneous transfer (SWIPT) is addressed. beamforming vectors, RIS reflection coefficients, split ratios are jointly optimized subject to maximum constraints, minimum realistic constraints on...

For machining workshops that use automated guided vehicles (AGVs) for material handling and management, workstation layout AGV path are coupling factors affecting the cost (MHC). The multi-row is a typical pattern in many workshops, currently, there lack of studies on problem (MRLP) while taking into account path. This study established bi-objective optimization methodology integrating to minim...

This paper presents a modified Differential Evolution (DE) algorithm called OCMODE for solving multi-objective optimization problems. First, the initialization phase is improved by using the opposition based learning. Further, a time varying scale factor F employing chaotic sequence is used which helps to get a well distributed Pareto front by the help of non dominated and crowding distance sor...

Several indicator-based evolutionary multiobjective optimization algorithms have been proposed in the literature. The notion of optimal μ-distributions formalizes the optimization goal of such algorithms: find a set of μ solutions that maximizes the underlying indicator among all sets with μ solutions. In particular for the often used hypervolume indicator, optimal μ-distributions have been the...