Building Maintenance plays an important role throughout the building lifecycle from devis-ing conceptual plans to the end. Due to the high cost of building maintenance and the direct impact of maintenance effectiveness on the quality of life of building occupants, special attention must be devoted. One of the most important issues in this field is building maintenance contractor selection. This issue becomes even more critical in public buildings, such as hospitals, offices, and military centers. The purpose of this study is to present a method that can be used to select the contractor in such a way that the response robustness is high and the employed method is the most accurate one among other similar methods. To do this, the contractors are ranked by 7 multi-criteria decision-making methods. Then, the Spearman correlation coefficients are obtained for each pair of methods. When there is a significant difference between the outcomes of the methods, the output of each method is compared with the output of the Artificial Neural Network (ANN) model. The method with the least difference with the neural network output is taken as the superior method. After selecting the best method, a robustness analysis is performed on it to verify the stability of the answer. The proposed model is implemented on a real case study. Statistical analysis shows that the implementation of this method has increased the satisfaction of the residents.

This paper analyzes the choice of a PISA selector for a Hybrid Algorithm integrating it as a Multi-Objective Evolutionary Algorithm (MOEA) with a path-dependent search algorithm. The interaction between these components provides an efficient procedure for solving Multi-Objective Problems (MOPs) in operations scheduling. In order to choose the selector, we consider both NSGA and SPEA as well as their successors (NSGAII and SPEAII). NSGAII and SPEAII are shown to be the most efficient candidates. On the other hand, for the path-dependent search at the end of each evolutionary phase we use the multi-objective version of Simulated Annealing.

One of the most important methods for building good marketing strategy is to learn more about existing competitors, suppliers, etc. This paper presents an empirical investigation to study the relationship between wholesalers, bargaining pricing, new rivals and pricing strategy on preparing appropriate marketing strategy in meat market in city of shiraz, Iran. The proposed study designs a questionnaire in Likert scale and distributes it among 200 experts in this market. Cronbach alpha has been calculated as 97.3%, which validates the overall survey. The results of the implementation of Pearson correlation ratio indicate that there were some positive and meaningful relationships between all components of the survey with marketing strategy.

Computer TCP/IP networks are becoming critical in all aspects of life. As computer networks continue to improve, the levels of redundancy continue to increase. Modern network redun-dancy features can be complex and expensive. This leads to misconfiguration of the redun-dancy features. Monitoring everything is not always practical. Some redundancy features are easy to detect while others are more difficult. It is common for redundancy features to fail or contribute to a failure scenario. Incorrectly configured redundancy will lead to network downtime when the network is supposed to be redundant. This presents a false sense of se-curity to the network operators and administrators. This research will present two scenarios that are commonly left unmonitored and look at a practical way to deploy solutions to these two scenarios in such a way that the network uptime can be improved. Implementing a practical approach to monitor and mitigate these types of failures allows costs spent on re-dundancy to increase uptime, and thus increase overall quality that is critical to a modern digital company.

Positive affectivity and affective management are among important issues for the most desirable effectiveness of employees in the workplace. Accordingly, in this research, the role of meaning and spirituality at workplace is considered for job happiness, positive affect and job satisfaction. To this end, within a correlation study, with the selection of two hundred and four employees of two custom organizations in Esfahan and Tehran, in Iran, who answer meaning and spirituality at work, job happiness, positive affect and job satisfaction questionnaires, the research hypotheses have been tested through Pearson & apos; s correlation and structural equation modeling. The results showed that there were significant relationships between meaning and spirituality at work, job happiness, positive affect and job satisfaction. Results of structure equation modeling revealed that during two chain models, at first meaning and spirituality at work are linked to job happiness and positive effect. Then job happiness and positive effect cause reinforcement of job satisfaction. The results of this study showed that meaning and spirituality at work cause positive affective spillover from job happiness and positive affect to job satisfaction.

Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM) methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH) is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

Cell formation process is one of the first and the most important steps in designing cellular manufacturing systems. It consists of identifying part families according to the similarities in the design, shape, and presses of parts and dedicating machines to each part family based on the operations required by the parts. In this study, a hybrid method based on a combination of simulated annealing algorithm and dynamic programming was developed to solve a bi-objective cell formation problem with duplicate machines. In the proposed hybrid method, each solution was represented as a permutation of parts, which is created by simulated annealing algorithm, and dynamic programming was used to partition this permutation into part families and determine the number of machines in each cell such that the total dissimilarity between the parts and the total machine investment cost are minimized. The performance of the algorithm was evaluated by performing numerical experiments in different sizes. Our computational experiments indicated that the results were very encouraging in terms of computational time and solution quality.

There are many evidences to believe that investors’ personal characteristics influence on their financial decisions when they purchase stocks, bounds, etc. In this paper, we present an empirical investigation to study the effects of 20 personal characteristics on 52 managers of mutual funds in Iran. Using Pearson correlation test, the study has detected that seven factors including anchoring & adjustment, framing, over confidence, illusion of control, hindsight, recency and self-attribution positively influence on investors’ behaviors. In addition, five factors including consistency, self-control, loss aversion, regret aversion and availability negatively influence on investors’ behaviors. However, the study did not find any evidence to confirm any kind of relationship of representativeness, conservatism, ambiguity aversion, optimism, mental accounting, confirmation and status quo on investors’ behaviors.

This paper performs an empirical investigation on employees’ business intelligence and customer relationship management and their effects on customer satisfaction. The proposed study has been implemented among 625 people, 240 sales representative and 385 regular customers, who are involved with products of an Iranian automaker named Iran Khodro. The proposed study designs three questionnaires in Likert scale for business intelligence, customer relationship management and customer satisfaction and Cronbach alpha have been calculated for these three questionnaires as 0.85, 0.84 and 0.78, respectively. The study distributes the questionnaires among groups, employees as well as customers, and using one-way t-student test as well as regression technique the study finds that business intelligence and customer relationship management are within an acceptable limit (P & LT; 0.01) and they positively influence on customers’ satisfaction (P & LT; 0.01).

For many years, supplier selection as an important multi-criteria decision has attracted both the researchers and practitioners. Recently, high incidences of natural disasters, terrorism attacks, labor strikes, and other kinds of risks, also known as disruptions, indicate the vulnerability of procurement process to these unpredicted events. In this study, a new framework is introduced to select suppliers while considering the supply risks. In the proposed framework, an expert is asked to determine the reliability of each procurement element (i.e., production, transportation, and communication) based on some proposed risk factors. Then, a distinct Multi-Layer Perceptron (MLP) network is trained to play the role of the expert opinion for estimating the reliability scores of each procurement. In addition to reliabilities, the Data Envelopment Analysis (DEA) is used to take into account the conventional selection criteria: price, delivery, quality, and capacity. A set of Pareto-optimal suppliers is obtained from the combination of efficiencies and reliability scores. Finally, the decision maker is recommended to choose between the non-dominated suppliers. Obtained experiment results indicate the effectiveness of the proposed framework.