Evaluating corporate social responsibility of airlines using entropy weight and grey relation analysis

This paper applies entropy weight and grey relation analysis to evaluate corporate social responsibility (CSR) performance of eight Chinese major airlines. This paper intends to achieve two main aims. First, this study uses entropy to find the relative weights of performance measures of CSR. In so doing, we find that on-time performance, accident rate, flight frequency, growth of employees revenue, and employees revenue are relatively most important measures. Second, based on the results of entropy analysis, this study ranks the airlines in terms of CSR performance by grey relation analysis. This result shows that most of the larger state-controlled airlines perform better in performance of CSR. Furthermore, the private airline has made relatively large improvement in its CSR performance. In addition, the listed airlines are better than non-listed airlines in CSR performance.     

Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm

This paper presents a bi-objective VMI problem in a single manufacturer-single vendor multi-retailer (SM-SV-MR) supply chain, which a redundancy allocation problem is incorporated. In the hybridized problem, a manufacturer produces a single item using several machines that work in series, and stores it in a warehouse to replenish one vendor who delivers it to several retailers using the shortest possible route. A novel meta-heuristic, called hybrid bat algorithm (HBA), with calibrated parameters is utilized to find a near-optimum solution. To show the efficiency of HBA, the results are compared to the ones using the traditional BA and a genetic algorithm.