Mixed-Integer Linear Programming Approach for Life-Cycle Carpet Profit

This paper proposes an mixed-integer linear programming (MILP) model to accurately represent a product life-cycle design considering profit maximization. The model that takes into account the effects on the demand lev-el and a measure of the customer utility considering recycled raw materials and prices of the traditional and modular products. Demand functions for traditional and modular products are considered. Given the presence of bilinear terms in the formulation (for example due to the multiplication of product price for the demand), the multi-parametric disaggregation technique is used to obtain a line-ar model. The developed model is applied to a company that produces tradition-al carpets and it wants to manufacture carpets based on a new modular design where recycled materials must be incorporated. The objective of the company is to maximize the total profit taking into account the design specifications and the selling prices for traditional and modular carpets. In addition, the amount of square meters of traditional carpets must be determined and the take-back rate must be considered. The practical behavior of the formulation is analyzed through computational experiments exploring the analyzed case-study.Sociedad Argentina de Informática e Investigación Operativ

Mixed-Integer Linear Programming Approach for Life-Cycle Carpet Profit

This paper proposes an mixed-integer linear programming (MILP) model to accurately represent a product life-cycle design considering profit maximization. The model that takes into account the effects on the demand lev-el and a measure of the customer utility considering recycled raw materials and prices of the traditional and modular products. Demand functions for traditional and modular products are considered. Given the presence of bilinear terms in the formulation (for example due to the multiplication of product price for the demand), the multi-parametric disaggregation technique is used to obtain a line-ar model. The developed model is applied to a company that produces tradition-al carpets and it wants to manufacture carpets based on a new modular design where recycled materials must be incorporated. The objective of the company is to maximize the total profit taking into account the design specifications and the selling prices for traditional and modular carpets. In addition, the amount of square meters of traditional carpets must be determined and the take-back rate must be considered. The practical behavior of the formulation is analyzed through computational experiments exploring the analyzed case-study.Sociedad Argentina de Informática e Investigación Operativ

Mixed-Integer Linear Programming Approach for Life-Cycle Carpet Profit

This paper proposes an mixed-integer linear programming (MILP) model to accurately represent a product life-cycle design considering profit maximization. The model that takes into account the effects on the demand lev-el and a measure of the customer utility considering recycled raw materials and prices of the traditional and modular products. Demand functions for traditional and modular products are considered. Given the presence of bilinear terms in the formulation (for example due to the multiplication of product price for the demand), the multi-parametric disaggregation technique is used to obtain a line-ar model. The developed model is applied to a company that produces tradition-al carpets and it wants to manufacture carpets based on a new modular design where recycled materials must be incorporated. The objective of the company is to maximize the total profit taking into account the design specifications and the selling prices for traditional and modular carpets. In addition, the amount of square meters of traditional carpets must be determined and the take-back rate must be considered. The practical behavior of the formulation is analyzed through computational experiments exploring the analyzed case-study.Sociedad Argentina de Informática e Investigación Operativ

International multicenter observational study on assessment of ventilatory management during general anaesthesia for robotic surgery and its effects on postoperative pulmonary complication (AVATaR) : study protocol and statistical analysis plan

Introduction: Robotic-assisted surgery (RAS) has emerged as an alternative minimally invasive surgical option. Despite its growing applicability, the frequent need for pneumoperitoneum and Trendelenburg position could significantly affect respiratory mechanics during RAS. AVATaR is an international multicenter observational study aiming to assess the incidence of postoperative pulmonary complications (PPC), to characterise current practices of mechanical ventilation (MV) and to evaluate a possible association between ventilatory parameters and PPC in patients undergoing RAS. Methods and analysis: AVATaR is an observational study of surgical patients undergoing MV for general anaesthesia for RAS. The primary outcome is the incidence of PPC during the first five postoperative days. Secondary outcomes include practice of MV, effect of surgical positioning on MV, effect of MV on clinical outcome and intraoperative complications. Ethics and dissemination: This study was approved by the Institutional Review Board of the Hospital Israelita Albert Einstein. The study results will be published in peer-reviewed journals and disseminated at international conferences. Trial registration number: NCT02989415; Pre-results