Credibility-Based Biobjective Fuzzy Optimization for Supplier Selection Problem with Disruption

This paper addresses a supplier selection problem in which a buyer procures multiple products from multiple suppliers under disruption risk. The problem is formulated as a new credibility-based biobjective fuzzy optimization model. In the proposed model, cost, capacity, and demand are characterized by fuzzy variables with known possibility distributions. The objectives of our model are to maximize the total quality of purchased products and minimize the expected total cost. Two credibility constraints are used to guarantee that the chance about the supplier capacity and buyer demand can satisfy the predetermined levels. The main concern in solving the optimization model is to calculate the expected value of the objective function and the credibility in the constraints. When the key parameters are mutually independent triangular fuzzy variables, the expected cost objective and credibility constraints can be transformed into their equivalent forms. Taking advantage of the structural characteristics of the equivalent model, the goal programming method is employed to solve the supplier selection model, which can be solved by conventional optimization method. At last, some numerical experiments have been performed to illustrate the effectiveness of the proposed model and solution strategy

Efficacy and safety of ciprofol for long-term sedation in patients receiving mechanical ventilation in ICUs: a prospective, single-center, double-blind, randomized controlled protocol

Introduction: Critically ill patients who receive mechanical ventilation after endotracheal intubation commonly experience discomfort and pressure. The major sedative drugs that are currently used in clinical practice present with many complications, such as hypotension, bradycardia, and respiratory depression. Ciprofol (HSK3486), which is a newly developed structural analog of propofol, is a short-acting gamma-aminobutyric acid (GABA) receptor agonist, and its mechanism of action is sedation or anesthesia by enhancing GABA-mediated chloride influx. The high efficacy of ciprofol for short-term sedation is comparable to that of propofol, and it has a relatively low incidence of adverse effects and high level of safety, which has been confirmed by multiple clinical studies. However, few studies have examined its safety and efficacy for long-term sedation. The purpose of the study is to evaluate the efficacy and safety of ciprofol for long-term sedation in mechanically ventilated patients.Methods: A prospective, single-center, double-blind, randomized, propofol-controlled, non-inferiority trial is proposed. The study will enroll 112 mechanically ventilated patients hospitalized in the intensive care unit (ICU) of the Shanghai Fourth People’s Hospital affiliated with Tongji University based on the inclusion and exclusion criteria of the study, and randomly assign them to a group sedated with either ciprofol or propofol. The primary outcome is the percentage of time spent under target sedation, and secondary outcomes include drug dose, number of cases requiring additional dextrometropine, incidence of systolic blood pressure <80 or >180 mmHg, incidence of diastolic blood pressure <50 or >100 mmHg, incidence of heart rate <50 beats per minute (bpm) or >120 bpm, inflammatory indicators, blood lipid levels, liver and kidney functions, nutritional indicators, ventilator-free days within the 7-day period after enrollment, 28-day mortality, ICU stay duration, and hospitalization costs.Discussion: We hypothesize that the efficacy and safety of ciprofol for long-term sedation in mechanically ventilated ICU patients will not be inferior to that of propofol.Trial registration: Chinese Clinical Trials Registry identifier ChiCTR2200066951

Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method

Optimal Decisions for Prepositioning Emergency Supplies Problem with Type-2 Fuzzy Variables

Prepositioning emergency supplies serves an important function in disaster relief operations. This paper presents a new class of fuzzy prepositioning emergency supplies model for three-echelon humanitarian logistics network, in which the postdisaster acquisition and transportation costs, the suppliers’ supply, and affected areas’ demand are uncertain and characterized by type-2 fuzzy variables with known possibility distributions. Since the inherent complexity of fuzzy prepositioning problem may be troublesome, the existing methods are no longer effective in dealing with the proposed model directly. We first derive the optimistic and pessimistic values formula for credibility value-at-risk (CVaR) reduced fuzzy variable of type-2 trapezoidal fuzzy variable. On the basis of formula obtained, we can convert original fuzzy prepositioning model into its equivalent parametric mixed integer programming form, which can be solved by conventional algorithms or general-purpose software. Finally, some numerical experiments have been performed to illustrate the effectiveness of the proposed model and solution strategy

Minimum Risk Facility Location-Allocation Problem with Type-2 Fuzzy Variables

Facility location decision is basically viewed as a long-term strategy, so the inherited uncertainty of main parameters ought to be taken into account in order to make models applicable. In this paper, we examine the impact of uncertain transportation costs and customers’ demands on the choice of optimal location decisions and allocation plans. This leads to the formulation of the facility location-allocation (FLA) problem as a fuzzy minimum risk programming, in which the uncertain parameters are assumed to be characterized by type-2 fuzzy variables with known type-2 possibility distributions. Since the inherent complexity of type-2 fuzzy FLA may be troublesome, existing methods are no longer effective in handling the proposed problems directly. We first derive the critical value formula for possibility value-at-risk reduced fuzzy variable of type-2 triangular fuzzy variable. On the basis of formula obtained, we can convert original fuzzy FLA model into its equivalent parametric mixed integer programming form, which can be solved by conventional numerical algorithms or general-purpose software. Taking use of structural characteristics of the equivalent optimization, we design a parameter decomposition method. Finally, a numerical example is presented to highlight the significance of the fuzzy FLA model. The computational results show the credibility and superiority of the proposed parametric optimization method

Modeling fuzzy data envelopment analysis under robust input and output data

This paper offers a fuzzy optimization framework for data envelopment analysis (DEA) to evaluate the relative efficiency of decision making units (DMUs) with parametric interval-valued fuzzy variable-based inputs and outputs. The parametric interval-valued fuzzy variable-based inputs and outputs is employed to capture the uncertainty of data on the basis of professional judgements or empirical estimations. The DEA problem is formulated as fuzzy expectation model with credibility constraints. When the inputs and outputs are mutually independent parametric interval-valued triangular fuzzy variables, we investigate the parametric equivalent representations of expectation objective function and chance constraints. In order to find the optimal solution of our DEA model, a domain decomposition method is proposed. Finally, the numerical example on the sustainable supplier evaluation and selection problem is provided to demonstrate the efficiency of the proposed DEA model and domain decomposition method

Performance evaluation of China\u27s railway passenger transportation sector

This research paper builds a dynamic network SBM (DNSBM) model to deconstruct China\u27s railway passenger transportation sector into transporting division and income-translated division. The two division are linked to each other by passenger volume and transportation income. The results show that the overall average efficiency value of China\u27s railway passenger transportation sector is 0.629, with transporting efficiency of 0.717 and income-translated efficiency of 0.625. Although the passenger volume and transportation income need to be increased, the performance of transportation income is worse due to price regulation. More importantly, the paper finds that the increase in total factor productivity (TFP) of this transportation sector is almost attributed to the enhanced TFP from frontier progress in the railway transporting process, whereas the income-translated process and the technical efficiency of transporting process are associated with productivity loss. Hence, apart from revision of inputs misallocation, this paper proposes that the development policies in China\u27s railway passenger transportation sector should take into account the role played by the market and deregulate price