Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.

In recent years, maintenance has been recognized as an effective and a significant improvement tool in the performance of equipments. Maintenance plays an important role in maintaining reliability, availability and quality of products, risk reduction, efficiency increase and safety, so maintenance and its strategies have a special place in the industry. A lot of researches show the necessity of using fuzzy sets in decision making problems due to its high flexibility. The choosing maintenance strategy is also a problem with so many uncertainties so using fuzzy sets seems to be very useful. The aim of this research is to provide a suitable mathematical decision making model for assessment and selection maintenance strategies by using hierarchical fuzzy Axiomatic Design (HFAD) and hierarchical fuzzy Topsis (HFTOPSIS) in Haft Almas Co. Since many criteria such as added value, safety, and … so are vital in the maintenance strategy selection, in this article first these criteria are investigated in the literature review and expert's opinions, then for obtaining the weights of criteria the FAHP method is used and finally the strategies are ranked through the applying HFAD and HFTOPSIS. The results of FTOPSIS and FAD were compared in selecting a maintenance strategy. The results of comparisons indicate the similarity of rankings by two techniques. Above techniques show that TPM alternative has superior to other strategies.

The most important concern for organizations, today, is the formulation and implementation of strategies which guarantees the success and survival of the firm in turbulent and complex environmental circumstances. This research seeks to propose a framework for strategy formulation in organizations. The case we examined in this paper is Mozhd E Vasl. This research is a kind of descriptive analytical. After studying mission statement, we identified the internal and external factors affecting the performance of the firm and formed internal factor evaluation matrix and external factor evaluation matrix. With respect to the information achieved in previous steps, we used SWOT matrix and internal-external matrix for comparison and adoption. After that, we applied position evaluating and strategic act to identify possible strategies. In the next step, we used qualitative strategic planning matrix and Fuzzy TOPSIS technique and Fuzzy SAW in order to rank the proposed strategies and at last we select the best strategy combining the results gained. Finally, this research concluded that seven competitive strategies have been selected, and the results showed product development is the first priority for improvement of strategy status in this manufacturing plant.

This paper describes Risk Based Inspection (RBI) methodology which is constructed in one of the units of Tehran Oil Refinery, (ISOMAX unit). The result of RBI Execution is a risk matrix which is constructed with Probability of Failure and Consequence of Failure. To define risk, probability of failure and consequence of failure and active damage mechanism were recognized. Riskwise software was assisted for implementing RBI. All equipment categorized into 3 main risk area based on the RBI results which were high risk, medium risk and low risk. High risk area is separated to Toxic and Non-Toxic area. As a result 4 risk area was considered. In addition an application of the Analytical Hierarchy Process (AHP) to select the most practicable maintenance strategy for equipment which is located in each risk area is described. To arrange the hierarchic structure & evaluation, four main criteria were defined (safety, cost, value added, feasibility) for pairwise judgments. Four possible alternatives are considered to complete the model, preventive, corrective, condition based and reliable centered maintenance.

In order to invest properly and identify the right short and long positions, the existence of an efficient strategy is necessary. Pairs trading system is one of the most famous algorithmic trading systems. In this system, a pair of stocks that have same trend in the long-time (reversion to the mean) and have fluctuations (spread) in the short-time is used. The most important point is to identify such a pair of stock. In this research, an approach is used to identify pairs of stocks and also to find the right short and long positions in trading pairs. In the first step, a stock pair that has a long-time statistical relationship is selected. The DTW method is used to calculate the distance between each stock pair and their movement similarity. Then, the hierarchical clustering method is used to cluster stocks, and then pairs of stocks that have a greater degree of similarity are selected. In the second step, the SVM method is used to identify buying and selling positions. In order to check the performance of the method, the S&P 500 index, which includes the top 500 stocks of the New York Stock Exchange, has been used.

Introduction: This paper offers an investigation into the strategies of selecting advertising media, based on consumer behavior. Our primary axiom is to accept the fact that this is a competitive world, in which only those organizations, which make their decisions and acts strategic and choose the best possible strategies will be successful and will survive. One of the key issues that organizations are facing with is the choice of an appropriate strategy for advertising. With the same token, one of the essential parts of the advertising strategy is the strategy of selecting an appropriate media for advertising. Accordingly, the main objective of this paper is to provide a scientific approach to the selection of advertising media from among various advertising companies. We also wanted primarily study various types of media in a company operating in the field of automotive parts industry. Secondary objectives of our research included: studying the impact of the target audiences on the selection of media, rankings various media in the industry in terms of access to audiences, and allocating the budget between various media by an imaginary (hypothetical) company in the automotive industry. We utilized the concept of media allocation in our research, in order to study the strategy of selecting advertising media. To do so, we evaluated advertising media in four categories as follows: television, radio, newspapers, and the internet. First, through using a telephone questionnaire we determined the level of audiences’ attention given to each of the target media. Then, using the output of the first stage, multi objective linear programming model was implemented for the media allocation. The paper includes problem statement, theoretical framework (which presents a review on the concept of advertisement, and then presents the theories on media allocation and related approaches in this field), research methodology, analysis of findings, and conclusions and discussion. Theoretical framework: Scholars have offered several explanations and definitions on advertisement strategies. The choice of advertising media is a common point, which is noted in the majority of these definitions. To plan an advertisement program, marketing manager should make five decisions which involve: determining advertising mission, determining advertising budget (money), determining advertising message, selecting media, and evaluating the advertisement (measurement). Accordingly, an integral component of advertisement is to select the advertising media. Advertising media is a communication tool that is responsible to transmit messages to a group of audience. Various categories of advertising media have been proposed by previous studies. These categories include various types of media such as television, radio, newspaper, billboard, print, and email advertising. Because there is a variety of media in place for managers to choose from, the subject of media allocation is very determining. Media allocation is the selection of appropriate media and the calculation of costs or the number of advertisement cases in each media. Media allocation should be applied so that the message reaches the target audience. Accordingly, to select advertising media the field of activity of advertising company should be considered. In addition, the media preferences of target audiences and consumers should be taken into account, and it would be determined based on the question of which media can better cover wider range of consumers. When reviewing the literature we realized that the majority of models on media allocation are quantitative models. Quantitative models in the literature which have been used to solve the problem of media budget allocation are classified into simulation, heuristic, and multi criteria decision making. Some studies have used a combination of such methods. Among the quantitative methods used whether in theoretical and/or in practical studies on advertising media allocation, we noticed that multi criteria decision making models have been used more than other types of statistical programming approaches. Among the multi criteria decision making models, linear programming model is more common. In view of the theoretical basis, this research aimed at utilizing the multi objective linear programming model for the allocation of advertising media. Our hypothesis is that the multi objective linear programming model is a suitable model for media allocating. Research Methodology: The research methodology of this study included two different steps. Firstly, through using a telephone questionnaire we evaluated the population of consumers in the automotive parts industry and determined the level of audiences’ attention paid to each of the four targeted media i. e. television, radio, newspapers, and internet. In this part of the study, car owners were selected as the target audience. Samples were randomly selected from among all car owners in Iran. After determining the sample size, which amounted to one hundred and eighty-five individuals, we decided to increase the reliability and accuracy through increasing the number of samples. That was the reason that the final sample size increased to one thousand and six hundred and six people. After collecting the data, we calculated the average time devoted to each of the desired media by the target population, and the percentage of target population that used each of the desired media. In the second step, using the output of the first stage, and taking into account the views of managers, multi objective linear programming model was implemented and media allocation was carried out via running the model. Conclusion and Discussion: Some of findings including the results of the telephone survey, indicates that the average times devoted to TV, Radio, newspapers, and Internet were 65. 74, 37. 67, 17. 52, and 9. 35 minutes, respectively. In addition, some tables were produced to show the percentage of people using a composite media. The results indicate that the percentage of people who use TV, Radio, newspapers, and Internet were 67. 47, 43. 3, 44. 42, and 8. 44 percent, respectively. Subsequently, we took into account the hypothetical limitations of the management-which included five limitations – and implemented multi objective linear programming model. According to the results of the model, from the total budget of fifteen billion Rials, 9 billion Rials had been allocated to television ads, 4. 2 billion Rials to radio, 1. 8 billion Rials to newspapers, and zero Rials to internet. According to the results of this study and based on the theoretical foundations, the selection of advertising media for companies should be based on the target population and audience in the target industry. It is of utmost importance to determine what type of media the target audience uses and which ones are more accessible to them. As was observed in this study, since TV media has taken the major part of attention of the target audience in the automotive industry, our model indicated that the highest amount of budget of the hypothetical company was also allocated to the same media.

IntroductionThe world faces sustainability challenges in economic, environmental, and social dimensions. Unsustainable consumption and production are causing serious social and economic crises, threatening life on Earth. Changing consumption and production patterns can protect natural resources. Green technology is crucial for sustainable development, but adopting it in business operations is challenging.  The rise of green branding has prompted companies to adopt eco-friendly practices. Research by Khandelwal et al., 2021 highlights increasing interest in green branding, emphasizing its importance in organizational strategies, including technology selection. Multi-Criteria Decision Making (MCDM) helps resolve problems with multiple conflicting criteria. The Analytic Hierarchy Process (AHP), designed by Saaty (1980), is preferred for technology selection. This research introduces a framework to integrate green branding goals into technology selection strategies. It uses multi-criteria decision-making methods and the analytic hierarchical process. A case study from the copper industry examines how these methods align technology selection with green branding at Babak Copper Company, known for its tank bioleaching method for copper production. Materials and MethodsThis paper presents a framework for technology evaluation, using the Iranian Babak Copper Company's adoption of Tank Bioleaching Technology to assess its alignment with green branding goals. MCDM, a field within operations research and management science, focuses on evaluating and selecting alternatives under conflicting criteria based on decision makers' preferences. It offers a structured process to evaluate multiple criteria simultaneously, aiding decision-makers in ranking and prioritizing alternatives. Common MCDM methods include AHP, which helps structure complex decisions hierarchically using pairwise comparison and consistency tests. MCDM and AHP support organizations in making strategic, responsible technology choices, enhancing operational efficiency, and fostering market competitiveness. A study by Sitorus et al. (2019) found that MCDM methods are frequently used in mining, with AHP being the most common. Among 90 reviewed articles, AHP was used in 26, and 17 of 41 hybrid MCDM articles combined AHP with other methods. The Iranian Babak Copper Company (IBCCO), based in Kerman province, aligns its technology choices with green branding goals, employing tank bioleaching technology to reduce environmental impact. This study evaluates bioleaching methods using AHP, considering IBCCO's green branding and business objectives. Five main copper ore bioleaching technologies are identified. Six key criteria for evaluation including sustainability, feasibility, efficiency, profitability, scalability, and innovation are selected based on literature review. Six mining experts provide pairwise comparison matrices, which are normalized and assessed for consistency using Expert Choice software. ResultsFor our final step, we are going to calculate the criterion weight by multiplying each criterion priority by the corresponding option priority. Then, we sum all the weighted criteria by option, having a final score for each option over the main goal. Discussion and ConclusionAfter evaluation utilizing the Analytic Hierarchy Process (AHP), it becomes evident that the tank bioleaching technology stands out as the optimal choice aligning with the objectives of the Babak Copper Company. The calculated AHP score for tank bioleaching, 0.366117, unequivocally supports the notion that the chosen technology resonates harmoniously with the company's mission. Illustrating through the case of IBCCO, which holds green branding as a paramount objective, this research deals with a comprehensive evaluation of the choice of copper cathode production technology within the company and its alignment with green branding aspirations. To facilitate the evaluation of manufacturing alternatives, this study introduces a comprehensive framework leveraging MCDM and AHP methods. The selection of this method is rooted in its prevalence in technology selection, particularly within the mining sector. Through the existing literature, bioleaching stands out as the environmentally preferable choice for copper extraction in contrast to other hydrometallurgy options, given its commercial and sustainability considerations. The subsequent step, involves the assessment of various bioleaching methods, including tank bioleaching, heap bioleaching, dump bioleaching, vat bioleaching and in-situ, all conducted through the AHP technique. This paper delves into the intricate interplay between green branding objectives and technology selection strategies. Through reviewing the existing literature on green branding, sustainable technology and technology selection strategies, this paper investigates their relationship. Moreover, future research avenues could delve into exploring the impact of green technology adoption on intangible assets and legal benefits. Furthermore, investigating the willingness of businesses and governments to pay a premium for green products could provide valuable insights. Lastly, assessing the long-term implications of reduced production costs in the tank bioleaching method is another area warranting exploration. In conclusion, the prioritization of green branding within the production sphere underscores the escalating significance of green manufacturing within the industry. Nevertheless, it's imperative to recognize that the pursuit of green branding objectives isn't devoid of challenges, and in some instances, a trade-off between profitability and sustainability may emerge. Nonetheless, this study demonstrates that enterprises can effectively integrate environmental and green aspirations alongside their core business objectives, signifying a progressive approach to confront the mounting imperative of green production within the industry.

In today’s businesses world, effective use of information technology (IT) has a significant role in the success of organizations. Outsourcing strategy is the process of determining whether or not to outsource and, if so, what to outsource. Outsourcing selection is the process of finding and evaluating potential outsourcing partners. Outsourcing implementation is where the relationship between outsourcing partners is defined and established. Consequently, selection of effective strategy for outsourcing is an important decision for managers. This strategy is also important in the Iranian banking industry, since there are different qualitative criteria and especial condition while banking managers are faced with some challenges. This article aims to study IT market in Iran. More specifically, it focuses on banking industry to determine proportionate criteria for Iranian banking system while suggesting a hierarchical model for IT outsourcing strategy. This model helps executive managers of the Iranian banking system to select the best IT outsourcing strategy.