Vector Optimization w.r.t. Relatively Solid Convex Cones in Real Linear Spaces

In vector optimization, it is of increasing interest to study problems where the image space (a real linear space) is preordered by a not necessarily solid (and not necessarily pointed) convex cone. It is well-known that there are many examples where the ordering cone of the image space has an empty (topological/algebraic) interior, for instance in optimal control, approximation theory, duality theory. Our aim is to consider Pareto-type solution concepts for such vector optimization problems based on the intrinsic core notion (a well-known generalized interiority notion). We propose a new Henig-type proper efficiency concept based on generalized dilating cones which are relatively solid (i.e., their intrinsic cores are nonempty). Using linear functionals from the dual cone of the ordering cone, we are able to characterize the sets of (weakly, properly) efficient solutions under certain generalized convexity assumptions. Toward this end, we employ separation theorems that are working in the considered setting.

A weight-homogenous condition to the real Jacobian conjecture in

It is known that a polynomial local diffeomorphism $(f,\, g): {\mathbb {R}}^{2} \to {\mathbb {R}}^{2}$ is a global diffeomorphism provided the higher homogeneous terms of $f f_x+g g_x$ and $f f_y+g g_y$ do not have real linear factors in common. Here, we give a weight-homogeneous framework of this result. Our approach uses qualitative theory of differential equations. In our reasoning, we obtain a result on polynomial Hamiltonian vector fields in the plane, generalization of a known fact.

JENSEN–MERCER INEQUALITY AND RELATED RESULTS IN THE FRACTAL SENSE WITH APPLICATIONS

The most notable inequality pertaining convex functions is Jensen’s inequality which has tremendous applications in several fields. Mercer introduced an important variant of Jensen’s inequality called as Jensen–Mercer’s inequality. Fractal sets are useful tools for describing the accuracy of inequalities in convex functions. The purpose of this paper is to establish a generalized Jensen–Mercer inequality for a generalized convex function on a real linear fractal set [Formula: see text] ([Formula: see text]. Further, we also demonstrate some generalized Jensen–Mercer-type inequalities by employing local fractional calculus. Lastly, some applications related to Jensen–Mercer inequality and [Formula: see text]-type special means are given. The present approach is efficient, reliable, and may motivate further research in this area.

On new generalized unified bounds via generalized exponentially harmonically s-convex functions on fractal sets

The visual beauty reflects the practicability and superiority of design dependent on the fractal theory. Based on the applicability in practice, it shows that it is the completely feasible, self-comparability and multifaceted nature of fractal sets that made it an appealing field of research. There is a strong correlation between fractal sets and convexity due to its intriguing nature in the mathematical sciences. This paper investigates the notions of generalized exponentially harmonically ($GEH$ G E H ) convex and $GEH$ G E H s-convex functions on a real linear fractal sets $\mathbb{R}^{\alpha }$ R α ($0<\alpha \leq 1$ 0 < α ≤ 1 ). Based on these novel ideas, we derive the generalized Hermite–Hadamard inequality, generalized Fejér–Hermite–Hadamard type inequality and Pachpatte type inequalities for $GEH$ G E H s-convex functions. Taking into account the local fractal identity; we establish a certain generalized Hermite–Hadamard type inequalities for local differentiable $GEH$ G E H s-convex functions. Meanwhile, another auxiliary result is employed to obtain the generalized Ostrowski type inequalities for the proposed techniques. Several special cases of the proposed concept are presented in the light of generalized exponentially harmonically convex, generalized harmonically convex and generalized harmonically s-convex. Meanwhile, an illustrative example and some novel applications in generalized special means are obtained to ensure the correctness of the present results. This novel strategy captures several existing results in the corresponding literature. Finally, we suppose that the consequences of this paper can stimulate those who are interested in fractal analysis.

Fuzzy Linear Programming Dalam Optimalisasi Pelayanan Air Bersih Perusahaan Daerah Air Minum (PDAM) Kab. Jeneponto Menggunakan Metode Sabiha

Abstrak. Fuzzy linear programing merupakan pengembangan model program linear dalam menentukan nilai optimal yang mengandung bilangan fuzzy. Metode yang dapat digunakan dalam menyelesaikan fuzzy linear programing yaitu metode Sabiha. Penggunaan metode Sabiha didasarkan pada bilangan linear fuzzy real yang berbentuk bilangan triplet. Pada penelitian ini digunakan model Fuzzy linear programing dalam menentukan nilai optimal pelayanan PDAM Kab. Jeneponto dengan metode sabiha. Menyusun setiap indikator fungsi tujuan (Z) dan fungsi kendala untuk dioptimalkan.. Hasil penyelesaian model diperoleh nilai optimal total pelanggan 9075,999999999990. Untuk setiap variabel tujuan dengan nilai optimal 8896, 999999999990 untuk jenis pelanggan rumah tangga, 96,0000000000112 untuk jenis pelanggan sosial khusus, dan 82,9999999999982 untuk jenis pelanggan sosial umum. Dengan total pendapatan optimal Rp. 4.753.125.000 dan total permintaan air 1.082.303 m3.Kata Kunci : Program Linear, Fuzzy Linear Programing, Linear Fuzzy Number. Metode Sabiha, Optimalisasi.Abstract. Linear fuzzy programing is advance model for linear programing to determin the optimal result that contains fuzzy numbers. Linear Fuzzy programing can be solved using Sabiha’s method. Which is based on real linear fuzzy numbers in triplet numbers form. This paper used linear fuzzy programming model and Sabiha’s method, to determin the optimal solution on PDAM Kab. Jeneponto’s operation plan. Each indicator constructed to optimized objective function and constraint function. Results of this research have optimal solution for each objective variable was obtained with an optimal value for total costumer are 9075,999999999990 from 8896,999999999990 the type of household customer, 96,0000000000112 the type of special social customer, and 82,9999999999982 the type of public social costumer. With an optimal total revenue Rp. 4,753,125,000 and total water demand 1,082,303 m3.Keywords: Linear Programing, Linear Fuzzy Programing, Linear Fuzzy Number, Sabiha’s Method, Optimalization.

Hydrogen-like Atoms

This chapter shows how the electronic Schrodinger equation (SE) is solved for a hydrogen-like atom, i.e. an electron moving in the field of a fixed point-like nucleus with charge number Z. The hydrogen atom corresponds to Z = 1. The potential in atomic units is –Z/r, with r being the distance of the electron from the nucleus. The SE is not separable in Cartesian coordinates, but in spherical polar coordinates it separates into a radial equation and an angular momentum equation. The bound states have a total energy of –Z2/(2n2), with n = nr + ℓ being the principal quantum number (q.n.), ℓ = 0,1,2,… the angular momentum q.n., and nr = 1,2,3,… being a radial q.n. Each state for a given ℓ is 2ℓ+1-fold degenerate, with the components labelled by the projection q.n. mℓ. The wavefunctions for mℓ ≠ 0 are complex, but real linear combinations can be formed. This gives the atomic orbitals known from general and organic chemistry. Different ways of visualizing the real wavefunctions are discussed, e.g. as iso-surfaces.

On a Certain Generalized Functional Equation for Set-Valued Functions

The aim of the paper is to generalize results by Sikorska on some functional equations for set-valued functions. In the paper, a tool is described for solving a generalized type of an integral-functional equation for a set-valued function F:X→cc(Y), where X is a real vector space and Y is a locally convex real linear metric space with an invariant metric. Most general results are described in the case of a compact topological group G equipped with the right-invariant Haar measure acting on X. Further results are found if the group G is finite or Y is Asplund space. The main results are applied to an example where X=R2 and Y=Rn, n∈N, and G is the unitary group U(1).