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This study aims to investigate the effects and implications of overconfidence in a competitive game involving multiple newsvendors. This study explores how overconfidence influences system coordination, optimal stocking strategies and competition among newsvendors in the context of the well-known newsvendor stocking problem.

The study applies robust optimization theory and the absolute regret minimization criterion to analyze the competitive game of overconfident newsvendors. This study considers the asymmetric information held by newsvendors regarding market demand and obtains a closed-form solution for the competing game. The effects of overconfidence on system coordination and optimal stocking strategies are examined.

The results of the study indicate that overconfidence can act as a positive force in reducing the effects of overstocking caused by competition and asymmetric information among newsvendors. The analysis reveals that there exists an optimal level of overconfidence that coordinates the ordering system of multiple overconfident newsvendors, leading to first-best outcomes under certain conditions. Additionally, numerical examples confirm the obtained results. Furthermore, considering newsvendors' expected profit, the study finds that a higher degree of overconfidence does not necessarily result in lower actual expected profit.

Despite the significant contributions of this study to theoretical and managerial insights, this study does have certain limitations. First, in the establishment of the belief demand function, the substitution ratio, which quantifies the transfer, is assumed to be an exogenous variable. However, in reality, this is often influenced by factors such as the price of goods and the distance between stores. Therefore, one direction worth studying in the future is to explore the uncertainty associated with the demand substitution ratio and integrate that as an endogenous variable into the optimization model. Second, this study does not address the type of product and solely focuses on quantitatively analyzing the effect of salvage value on the optimal stocking strategy. Future studies can explore the effect of degree of perishability and selling period of the product on the stocking. Third, the focus of uncertainty in this study revolves around market demand, and the implications of this uncertainty are significant. A recent study (Rahbari et al., 2023) addressed an innovative robust optimization problem related to canned foods during pandemic crises. The recent study's findings highlighted the effectiveness of expanding canned food exports to neighboring countries with economic justification as the best strategy for companies amidst the disruptions caused by the coronavirus disease 2019 (COVID-19) pandemic. Incorporating the issue of disruptions into the authors' research would be interesting and challenging.

From a managerial perspective, the authors' study provides a research paradigm for game-theoretic inventory problems in scenarios where the market demand distribution is unknown. While most inventory problems are analyzed and solved based on expectation-based optimization criteria, which rely on an accurate distribution of market demand, obtaining this information in practice can often be challenging or expensive for decision-makers. Consequently, a discrepancy arises between real-world observations and theoretical identifications. This study aimed to complement previous research and address the inconsistency between observations and theoretical identification.

The authors' research contributes to the existing understanding of overconfidence and assists individuals in making appropriate stocking strategies based on the individuals' level of overconfidence. Diverging significantly from the traditional view of overconfidence as a negative bias, the authors' results show the view's potential positive impact within a competitive environment, resulting in greater actual expected profits for newsvendors.

This study contributes to the existing literature by examining the effects of overconfidence in a competitive game of newsvendors. This study extends the analysis of the well-known newsvendor stocking problem by incorporating overconfidence and considering the implications for system coordination and competition. The application of robust optimization theory and the absolute regret minimization criterion provides a novel approach to studying overconfidence in this context.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Introduction Operations research, i.e. the application of scientific methodology to operational problems in the search for improved understanding and control, can be said to have started with the application of mathematical tools to military problems of supply bombing and strategy, during the Second World War. Post‐war these tools were applied to business problems, particularly production scheduling, inventory control and physical distribution because of the acute shortages of goods and the numerical aspects of these problems.

The purpose of this paper is to achieve high‐performance aerofoils that enable delayed stall conditions and achieve high lift to drag ratios.

The unsteady Reynolds averaged Navier‐Stokes equations are employed in conjunction with a shear stress transport (κ‐ω) turbulence model. A control equation is designed and implemented to determine the temporal response of the actuator. A rotating element, in the form of an actuator disc, is embedded on the leading edge of NACA 0012 aerofoil, to inject momentum into the wake region. The actuator disc is rotated at different angular speeds, for angles of attack (α) between 00 and 240.

Phenomena such as flow separation, wake vortices, delayed stall, wake control, etc. are numerically investigated by means of streamlines, streaklines, isobars, etc. Streamwise and cross‐stream forces on the aerofoil are obtained. The influence of momentum injection parameter (ξ) on the fluid flow patterns, and hence on the forces acting on the streamlined body are determined. A synchronization‐based coupling scheme is designed and implemented to achieve annihilation of wake vortices. A delayed stall angle resulted with an attendant increase in maximum lift coefficient. Due to delay and/or prevention of separation, drag coefficient is also reduced considerably, resulting in a high‐performance lifting surface.

The practicality of momentum injection principle requires both wide ranging and intensive further studies to move forward beyond the proof of concept stage.

Determination of forces and moments on an aerofoil is of vital interest in aero‐dynamic design. Perhaps, runways of the future can be shorter and/or more pay load can be carried by an aircraft, for the same stall speed.

The paper describes how a synchronization‐based coupling scheme is designed and implemented along with the RANS solver. Furthermore, it is tested to verify the dynamic adaptability of the wake vortex annihilation for NACA 0012 aerofoils.

The purpose of this paper is to highlight the possibilities of a novel Lagrangian formulation in dealing with the solution of the incompressible Navier‐Stokes equations with very large time steps.

The design of the paper is based on introducing the origin of this novel numerical method, originally inspired on the Particle Finite Element Method (PFEM), summarizing the previously published theory in its moving mesh version. Afterwards its extension to fixed mesh version is introduced, showing some details about the implementation.

The authors have found that even though this method was originally designed to deal with heterogeneous or free‐surface flows, it can be competitive with Eulerian alternatives, even in their range of optimal application in terms of accuracy, with an interesting robustness allowing to use large time steps in a stable way.

With this objective in mind, the authors have chosen a number of benchmark examples and have proved that the proposed algorithm provides results which compare favourably, both in terms of solution time and accuracy achieved, with alternative approaches, implemented in in‐house and commercial codes.

The concepts of solution error and optimal mesh in adaptive finite element analysis are revisited. It is shown that the correct evaluation of the convergence rate of the error norms involved in the error measure and the optimal mesh criteria chosen are essential to avoid oscillations in the refinement process. Two mesh optimality criteria based on: (a) the equal distribution of global error, and (b) the specific error over the elements are studied and compared in detail through some examples of application.

There is an increasing interest in airfoils that modify their shape to adapt at the flow conditions. As an example of application, the authors search the optimal 4-digit NACA airfoil that maximizes the lift-over-drag ratio for a constant lift coefficient of 0.6, from Re = 10⁴ to 3 × 10⁶.

The authors consider a γ−Re_θt transition model and a κ – ω SST turbulence model with a covariance matrix adaptation evolutionary optimization algorithm. The shape is adapted by radial basis functions mesh morphing using four parameters (angle of attack, thickness, camber and maximum camber position). The objective of the optimization is to find the airfoil that enables a maximum lift-over-drag ratio for a target lift coefficient of 0.6.

The computation of the optimal airfoils confirmed the expected increase with Re of the lift-over-drag ratio. However, although the observation of efficient biological fliers suggests that the thickness increases monotonically with Re, the authors find that it is constant but for a 1.5 per cent step increase at Re = 3 × 10⁵.

The authors propose and validate an efficient high-fidelity method for the shape optimization of airfoils that can be adopted to define robust and reliable industrial design procedures.

The authors show that the difference in the numerical error between two-dimensional and three-dimensional simulations is negligible, and that the numerical uncertainty of the two-dimensional simulations is sufficiently small to confidently predict the aerodynamic forces across the investigated range of Re.