Nowadays, the main attention and tendencies of tourists are towards ecotourism and its related activities. Ecotourism centers are an active business in the ecotourism industry that provides necessary services for tourists. Today, the number of ecotourism centers in some areas is increasing and it caused an intensively competitive environment between these centers to attract customers. In other words, the big concern of the manager and owners of these centers is knowing the variables which affect the decisions of tourists to choose an ecotourism center. From what we know, no research has been done on this subject. Therefore, these matters encouraged us to do an essential investigation. In this paper, firstly, the factors affecting a tourist's decision to choose an ecotourism center are identified. Three types of customers (tourists) are considered for ecotourism centers and the weight of each of the considered factors is calculated using the fuzzy DEMATEL method based on the opinion of each customer group. Then, the factors are ranked using the TOPSIS method. The outcomes manifest that the personnel of the centers and the brand of each center have the most and the least impact on the selection process by the tourist, respectively.

For a production business, the measurement of safety inventory to be maintained during each step of a supply chain is a key concern and requires providing the clients an irregular state of management. The stock held should be small to reduce holding costs and capacity while maintaining the capacity to service customers in time to satisfy much, if not all, the demand. This paper discusses this issue by using a deterministic time structure and provides a measure of the security position of stock in supply chains for the overall network. First, prove that the overall problem is NP-hard. Then set up a couple of parameters that characterize an optimal overall network structure. To take care of these problems, a polynomial approximation is considered. An arrangement of computational tests to survey the execution of the general-network calculation and to decide how to set different parameters for the calculation is selected. In addition to the general network case, the two-layer network issues are considered. Also, a nonlinear model for determining the level of safety stock in different components of the supply chain to minimize the related safety stock costs is developed.

Robot navigation in dynamic unknown environments is a challenging issue in the field of autonomous mobile robot control. This paper presents a hybrid robust method for navigating an industrial robot in an environment that contains dynamic obstacles. The objectives are to find the shortest path, to minimize the energy consumption of robot, to make the smoothness of the generated paths and to tackle dynamic obstacles. Robots employed in industrial environments demand considerable autonomy and require high level of accuracy and manoeuvrability at the same time. Besides, no collision is tolerable along the way. A single-objective optimization method based on path criteria fails to satisfy all of the requirements. This paper proposes a hybrid algorithm including the whale optimization algorithm (WOA) for path planning, a learnable function approximation network for making smoothness of the generated paths and a fuzzy logic controller to avoid obstacle collision. In this algorithm, WOA optimizes the best path to be taken from the start to goal position. Once a sequence of points is candidate and segments of path are merged, a radial basis function is trained to provide a smooth movement path in the dynamic environment while trying to maximize the safety margin. To further improve the safety of navigation, a fuzzy-based obstacle avoidance algorithm is executed when the robot is placed in the vicinity of an obstacle. Fuzzy decisions are made based on values of distance information. The proposed hybrid method for path planning and obstacle avoidance issues was implemented and evaluated in dynamic environments including specific shaped obstacles. A GUI-based simulation platform was designed in Matlab environment for testing the proposed algorithm. Implementation results indicate that the proposed algorithm has yielded in smooth non-marginal goal-directed navigation with acceptable performance metrics. Meanwhile, collisions to dynamic obstacles were adaptively and non-rigidly avoided. Such a model-free hybrid algorithm for path planning and obstacle avoidance can improve autonomy in industrial operation and decrease computational complexity.

Availability and reliability of a manufacturing system are the most common indicators in the reliability engineering area to assess the quality and on-time deliveries of the products they produce. The purpose of this paper is to analyze the availability, reliability. failure metrics such as MTBF and MTTF, and also steady-state availability of a cooking oilproduction line using a Markov approach. The product line works in three consecutive shifts 24 hours a day, for which five main subsystems are identified for the analysis. The results show that the first shift has the best performance in terms of reliability while the second shift has the worst performance. To improve the reliability of the production line, a corrective maintenance policy is used. First, the critical components of the subsystems are identified using the Pareto charts, and then, by increasing the repair rates, the availability of the production line in all three shifts is increased.

The purpose of the article is to substantiate the theoretical positions and develop practical recommendations for the development of tools for analytical assessment of the competitiveness of an enterprise, taking into account the influence of the corruption component. It has been established that the main inalienable structural components of the analytical assessment of the competitiveness of enterprises on the market are: 1) the efficiency of the enterprise (in four components: financial and economic efficiency, commercial efficiency, production-technological efficiency, social efficiency); 2) the competitiveness of the enterprise’s products (includes calculation of such indicators as an integral indicator of product quality (useful effect), price of products, integral indicator of service quality and other additional (consumer) product parameters).

During the last decade, reverse logistics networks received a considerable attention due to economic importance and environmental regulations and customer awareness. Integration of leading and reverse logistics networks during logistical network design is one of the most important factors in supply chain. In this research, an Integer Linear Programming model is presented to design a multi-layer reverse-leading, multi-product, and multi-period integrated logistics network by considering multi-capacity level for facilities under uncertainty condition. This model included three objectives: maximizing profit, minimizing delay of goods delivering to customer, and minimizing returned raw material from suppliers. This research gives financial incentives to encourage customers in order to return their used product. Considering that the remaining value of used products is the main incentive of a company to buy second-handed goods, a dynamic pricing approach is determined to define purchase price for these types of products, and based on that, the percentage of returned products were collected by customers. In addition, in this study, parameters have uncertainty features and are vague; therefore, at first, they are converted into exact parameters and, then, because model is multi-objective, the fuzzy mathematical programming approach is used to convert multi-objective model into a single objective; finally, the model by version 8 of Lingo is run. In order to solve a large-sized model, a non-dominated sorting genetic algorithm II (NSGA-II) was applied. Computational results indicate the effect of the proposed purchase price on encourage customers to return the used products.

One of the main critical steps that should be taken during natural disasters is the assignment and distribution of resources among affected people. In such situations, this can save many lives. Determining the demands for critical items (i.e., the number of injured people) is very important. Accordingly, a number of casualties and injured people have to be known during a disaster. Obtaining an acceptable estimation of the number of casualties adds to the complexity of the problem. In this paper, a location-routing problem is discussed for urgent therapeutic services during disasters. The problem is formulated as a bi-objective Mixed-Integer Linear Programming (MILP) model. The objectives are to concurrently minimize the time of offering relief items to the affected people and minimize the total costs. The costs include those related to locations and transportation means (e.g., ambulances and helicopters) that are used to carry medical personnel and patients. To address the bi-objectiveness and verify the efficiency and applicability of the proposed model, the ε-constraint method is employed to solve several randomly-generated problems with CLEPX solver in GAMS. The obtained results include the objective functions, the number of the required facility, and the trade-offs between objectives. Then, the parameter of demands (i.e., number of casualties), which has the most important role, is examined using a sensitivity analysis and the managerial insights are discussed.

The selection and implantation of sufficient and appropriate continuous improvement strategy are the key success factors for improving firm performance and enhancement of competitive advantage on manufacturing industries. As a result special role are given to Continuous improvement programs such as Supply Chain Management (SCM), Six-Sigma, Total Quality Management (TQM), Kaizen, Just-in-Time (JIT) and Total Productive Maintenance (TPM) in a production system, which attain sustainable business environment and competitive advantage. Thus, the aim of the study is to study the challenges and trends of global competitiveness of basic metal industries, investigates the way of integrating continuous improvement tools and then developed an integrated continuous improvement model from TQM, JIT, and SCM to improve the global competitiveness of steel and metal industries. From numerous contentious improvement programs, we have to emphasize integrated SCM, JIT and TQM implementation on basic metal industries to improve competitive performance. Mainly the study was conducted through field observation, questioner, company reports used as primary data and literature review of research articles, books, manuals, magazines, and electronic-sources, which used as secondary data. The survey data is analyzed using descriptive analysis, SPCT (fishbone diagram).The result found that poor supply chain system, workforce, raw material uncertainty, energy fluctuation, outdated technology, manufacturing systems, financial and logistics problems were identified as the obstacles and influence the Ethiopian basic metal industry performance and global competitiveness. Thus, to tackle the problems an integrated continuous improving model was developed to improve the performance and global competitiveness of basic metal industries.

The purpose of this study is to identify the effective factors of optimal use of social media in the brand equity of startup companies. To this end, the researcher collected the required data using snowball sampling, protocol design, and exploratory interviews with sixteen university experts, the industry in this field, and senior managers of accelerator companies and startups. Maxqda 18 software was used to analyze the interviews. In the open coding process, the researcher first identified 170 codes and categorized them into 8 categories. Then, based on the theoretical literature and using the opinion of academic experts in axial coding based on Strauss and Corbin paradigm model, the relevant model was extracted and finally the selective coding was performed. To evaluate the validity of coding, Peer check method, the member check method and reliability by Field note were conducted. The results indicate that the main phenomena is using social media in startups and the communicational dimension as causal factors, cognitive dimension, and attitude in the position of strategies, brand characteristics as background factors, relational dimension, and rules and regulations as intervening factors and finally behavioral dimension were obtained as the consequences of the model.

Supply chain network design in perishable product has become a challenging task due to its short life time, spoilage of product in degradation nature and stochastic market demand. This paper focused on designing and optimizing model for perishable product in stochastic demand, which comprises multiple levels from producer, local collector, wholesaler and retailers. The ultimate goal is to optimize availability and net profit of all members in supply chain network model for avocado fruit under stochastic demand. The network model has considered the quality deterioration rate of the product with increased order of transportation time. The validity of developed model was tested with data collected from avocado supply chain network in Ethiopian market.