This paper presents a fuzzy multi-criteria decision-making (FMCDM) model by integrating both subjective and objective weights for ranking and evaluating the service quality in hotels. The objective method selects weights of criteria through mathematical calculation, while the subjective method uses judgments of decision makers. In this paper, we use a combination of weights obtained by both approaches in evaluating service quality in hotel industries. A real case study that considered ranking five hotels is illustrated. Examples are shown to indicate capabilities of the proposed method.

This study emphasizes that project scheduling and material ordering (time and quantity of an order) must be considered simultaneously to minimize the total cost, as setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. Hence, this paper mathematically formulates the model for the multi-mode resource-constrained project scheduling with material ordering (MRCPSMO) problem. In order to be more realistic, bonus and penalty policies are included for the project. The objective function of the model consists of four elements: the material holding cost, the material ordering cost, the bonus paid by the client and the cost of delay in the project completion. Since MRCPSMO is NP-hard, the paper proposes three hybrid meta-heuristic algorithms called PSO-GA, GA-GA and SA-GA to obtain near-optimal solutions. In addition, the design of experiments and Taguchi method is used to tune the algorithms' parameters. The proposed algorithms consist of two components: an outside search, in which the algorithm searches for the best schedule and mode assignment, and the inside search, which determines the time and quantity of orders of the nonrenewable resources. First, a comparison is made for each B Aria Shahsavar

The aim of this paper is to propose an integrated modeling framework that would help manufacturing managers for assessment, ranking, and analysis of the manufacturing systems. The proposed framework is based on Taguchi method that ranks and analyzes the manufacturing sectors by consolidating a set of management and organization productivity indicators. Sixty-one indicators were identified and classified in five categories, namely (1) financial, (2) customer satisfaction, (3) process innovation, (4) production process, and (5) organizational learning and growth. The mentioned indicators are related to organizational and managerial productivity and efficiency. Next, a test problem and a random sample of 12 indicators have been carried out for the two-digit International Standard Industrial Classification sectors of manufacturing systems. Principal component analysis (PCA), numerical taxonomy, and clustering analysis approach have been used to demonstrate and validate the results of the integrated Taguchi method. Also, Spearman and Kendall tau correlation experiments should show high level of correlation between the findings of Taguchi, PCA, and taxonomy. In addition, normality test has been applied to show the superiority of integrated method over previous approaches. The proposed method has been provided with respect to management and organizational performance indicators to decide the best actions for continuous improvement. The results indicated that the structure and modeling approach of this paper could be easily utilized for managerial and organizational ranking and analysis of other sectors.

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