Probability maximization models for portfolio selection under ambiguity

Portfolio selection problem, Stochastic programming, Probability maximization model, Multi-scenario model,

Planning sustainable development through a scenario-based stochastic goal programming model

Most real-world optimization problems involve numerous conflicting criteria, imprecise information estimates and goals, thus the stochastic goal programming method offers an analytical framework to model and solve such problems. In this paper, we develop a stochastic goal programming model with satisfaction function that integrates optimal resource (labor) allocation to simultaneously satisfy conflicting criteria related to economic development, energy consumption, workforce allocation, and greenhouse gas emissions. We validate the model using sectorial data obtained from diverse sources on vital economic sectors for the United Arab Emirates. The results offer significant insights to decision makers for strategic planning decisions and investment allocations towards achieving long term sustainable development goals

Equilibrium analysis for common-pool resources

We present an aggregative normal form game to describe the investment decision making sit- uation for a CPR: we will consider a non-cooperative approach searching a Nash equilibrium of it, as well as a cooperative one searching a fully cooperative equilibrium. An application in the Environmental Economics will be illustrated and, in this context, we will introduce a threshold investment as a random variable and we will study the resulting game with aggregative uncertainty looking for a Nash equilib- rium and a fully cooperative equilibrium

Goal Programming Models for Managerial Strategic Decision Making

The Goal Programming (GP) model is an important Multiple Objective Programming (MOP) technique that has been widely utilized for strategic decision making in presence of competing and conflicting objectives. The GP model aggregates multiple objectives and allows obtaining satisfying solutions where the deviations between achievement and the aspirations levels of the attributes are to be minimized. The GP model is easy to understand and to apply: it is based on mathematical programming techniques and can be easily solved using software packages such as LINGO, MATLAB, and AMPL. The GP describes the spectrum of the Decision Maker’s preferences through a user-friendly and learning decision-making process. This chapter aims to present the state-of-the-art of GP models and highlight its applications to strategic decision making in portfolio investments, marketing decisions and media campaign

Surgical correction of Madelung’s deformity by combined corrective radioulnar osteotomy: 14 cases with four-year minimum follow-up

Fourteen wrists in 11 girls, mean age 13.3 years (range 9–16) at surgery, were treated for Madelung’s deformity. The presenting complaint was incapacitating pain. All were treated by radial closing wedge osteotomy and ulnar shortening osteotomy. The dorsal retinaculum was also surgically repaired in six cases. At a mean follow-up of 5.1 years (range 4–8.75), we observed improved range of motion in both flexion/extension and pronation/supination and absence of pain during daily activity. Radiographically, positioning of the distal radial articular surface and lunate subsidence were improved. Union was obtained after all osteotomies without secondary procedures. Posterior displacement of the ulnar head persisted in two wrists. Combined radioulnar osteotomy restored the anatomy to as near normal as possible. This technique provides satisfactory and encouraging results and does not compromise the surgical future of the wrist. However, longer follow-up is required to assess recurrence or possible long-term degenerative consequences