Penalty-based heuristic direct method for constrained global optimization

This paper is concerned with an extension of the heuristic DIRECT method, presented in[8], to solve nonlinear constrained global optimization (CGO) problems. Using a penalty strategy based on a penalty auxiliary function, the CGO problem is transformed into a bound constrained problem. We have analyzed the performance of the proposed algorithm using fixed values of the penalty parameter, and we may conclude that the algorithm competes favourably with other DIRECT-type algorithms in the literature.The authors wish to thank two anonymous referees for their comments and suggestions to improve the paper. This work has 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-UM

Understanding how the strategic similarities between energy companies influence the post-mergers and acquisitions performances

The energy sector has experienced rapid evolution in recent years, following the liberalization of the electricity and natural gas markets, driven by the European Union. These developments have led to a certain level of dynamism in Italy, particularly as concerns mergers and acquisitions (M&As) within the sector. This article examines the influence of strategic similarities between the target and bidder companies on their post-M&A performances. The model used involves a hierarchical regression relating the indexes of similarity between the merging companies, regarding their economic-financial management. The results reveal the influence of the strategic similarities and differences on the post-M&A performances of the companies, showing how the positive or negative effect depends on certain characteristics, such as their structure of share capital, business segments and size. The study evidences the strategic variables that should be considered in choosing the optimal target companies

A Gray-Box Approach for Curriculum Learning

Curriculum learning is often employed in deep reinforcement learning to let the agent progress more quickly towards better behaviors. Numerical methods for curriculum learning in the literature provides only initial heuristic solutions, with little to no guarantee on their quality. We define a new gray-box function that, including a suitable scheduling problem, can be effectively used to reformulate the curriculum learning problem. We propose different efficient numerical methods to address this gray-box reformulation. Preliminary numerical results on a benchmark task in the curriculum learning literature show the viability of the proposed approach

Geometric approach to Fletcher's ideal penalty function

Original article can be found at: www.springerlink.com Copyright Springer. [Originally produced as UH Technical Report 280, 1993]In this note, we derive a geometric formulation of an ideal penalty function for equality constrained problems. This differentiable penalty function requires no parameter estimation or adjustment, has numerical conditioning similar to that of the target function from which it is constructed, and also has the desirable property that the strict second-order constrained minima of the target function are precisely those strict second-order unconstrained minima of the penalty function which satisfy the constraints. Such a penalty function can be used to establish termination properties for algorithms which avoid ill-conditioned steps. Numerical values for the penalty function and its derivatives can be calculated efficiently using automatic differentiation techniques.Peer reviewe

Backyard poultry production in Chile: animal health management and contribution to food access in an upper middle-income country

Backyard production systems (BPS) that involve poultry are a good way to improve food security and poverty alleviation. Few studies have been carried out to quantify the contribution of poultry production to these households and the constraints they might face if a priority animal disease enters these systems. This study aims to characterize the poultry-rearing BPS in central Chile and to identify socio-economic factors associated to households’ consumption of poultry. Data was collected from 384 BPS through a face-to-face semi-structured questionnaire. Value chain framework associated with BPS poultry rearing and cash flow analysis of BPS was done to identify the inputs/outputs of the system and to know the profitability of the system. Multiple linear regression was performed to identify the BPS and household factors associated to poultry consumption. The results of this study suggest that BPS in central Chile have biosecurity deficiencies such as: lack of confinement, lack of veterinary assistance and incorrect handling of dead animals. Cash flow analysis indicated that 62% of the BPS had a positive balance from production. Distance to closest market and per capita income were factors associated to poultry value to farmers. Different factors were significant predictors of household poultry consumption. Positive predictors of consumption were identified as: (i) older owners, (ii) higher transportation price to closest market, (iii) larger flock size (iv) birds raised by women and (v) owning a car. On the contrary, (i) higher per capita income and (ii) bigger household size predicted a reduction in consumption. The results indicate the importance of BPS to low-income families and those living in remote areas while also highlighting the vulnerability of these systems to disease risks

Non-uniform doping across the Fermi surface of NbS2_2 intercalates

Magnetic ordering of the first row transition metal intercalates of NbS$_2$ due to coupling between the conduction electrons and the intercalated ions has been explained in terms of Fermi surface nesting. We use angle-resolved photoelectron spectroscopy to investigate the Fermi surface topology and the valence band structure of the quasi-two-dimensional layer compounds Mn$_{1/3}$NbS$_2$ and Ni$_{1/3}$NbS$_2$. Charge transfer from the intercalant species to the host layer leads to non-uniform, pocket selective doping of the Fermi surface. The implication of our results on the nesting properties are discussed

Filter-based DIRECT method for constrained global optimization

This paper presents a DIRECT-type method that uses a filter methodology to assure convergence to a feasible and optimal solution of nonsmooth and nonconvex constrained global optimization problems. The filter methodology aims to give priority to the selection of hyperrectangles with feasible center points, followed by those with infeasible and non-dominated center points and finally by those that have infeasible and dominated center points. The convergence properties of the algorithm are analyzed. Preliminary numerical experiments show that the proposed filter-based DIRECT algorithm gives competitive results when compared with other DIRECT-type methods.The authors would like to thank two anonymous referees and the Associate Editor for their valuable comments and suggestions to improve the paper. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundac¸ao para a Ciência e Tecnologia within the projects UID/CEC/00319/2013 and ˆ UID/MAT/00013/2013.info:eu-repo/semantics/publishedVersio

Fermi surface induced lattice distortion in NbTe2_2

The origin of the monoclinic distortion and domain formation in the quasi two-dimensional layer compound NbTe$_2$ is investigated. Angle-resolved photoemission shows that the Fermi surface is pseudogapped over large portions of the Brillouin zone. Ab initio calculation of the electron and phonon bandstructure as well as the static RPA susceptibility lead us to conclude that Fermi surface nesting and electron-phonon coupling play a key role in the lowering of the crystal symmetry and in the formation of the charge density wave phase