The continuous increase in energy consumption has brought worldwide attention to its significant environmental effect, which is triggered by the increase in greenhouse gas emissions, global warming, and rapid climate change. As such, more energy efficient buildings are required to minimize the energy consumption of heating and cooling. The present study introduces a set of machine learning-based models to predict the heating and cooling loads in buildings. This includes back-propagation artificial neural network, generalized regression neural network, radial basis neural network, radial kernel support vector machines and ANOVA kernel support vector machines. The comparisons were conducted as per mean absolute percentage error (MAPE), mean absolute error (MAE) and root-mean squared error (RMSE). Finally, the significance of the capacities of the machine learning models are evaluated using two-tailed student’s t-tests. Results demonstrate that the radial basis function network outperformed the aforementioned machine learning models.

A non-dominated sorting genetic algorithm (NSGA-II) is applied to obtain Pareto optimal solutions in widely used advanced machining processes, i.e., electric discharge machining, electrochemical micromachining, ultrasonic machining, abrasive water jet machining. The solutions obtained using the proposed method is in the form of the Pareto-optimal front, thus, any solution is acceptable and can be utilized to obtain optimum performance of the considered processes. The obtained results using NSGA-II show good agreement with the results of previous researchers. Implementation of the proposed method shows benefits to the process engineer of the industries as they can select alternative parameters based on the requirement.

Village tourism is one of the alternative forms of sustainable tourism that began to be developed in Bali. Bongkasa Pertiwi tourism village is one of the villages designated as a tourist village with a variety of natural potential. The purpose of this research is to analyze the strategy and development program of the Bongkasa Pertiwi Tourism Village, and to analyze the factors that play a role in the sustainability of the Bongkasa Pertiwi Tourism Village. The main data collection technique in this study is through FGD, the results of which are input to the SWOT and MICMAC analysis. The results of the SWOT analysis show that Bongkasa Pertiwi Tourism Village has strong category competitiveness, and high category attractiveness as a tourist village, so the strategic position of the development of the Kenderan tourism village is in the condition of growth and build. The three main factors in the sustainability of a tourist village are the uniqueness of the tourist village, the competence of human resources, and the presence of a driving force that has a link with stakeholders.

The paper studies the monetary approach to exchange rate for a group of five Pacific Basin economies, using quarterly data for the period of post – Asian financial crisis. Estimated results reveal that for Thailand and the Indonesia which were most affected by Asian financial crisis, monetary model did not work for explaining exchange rate movements. For Korea and Malaysia, the results show that there were long-run relationships between exchange rates and their monetary variables. However, the proportionality hypothesis of exchange rate to relative money supply did not hold for the two countries. Conversely, for Vietnam, it appears that the monetary model worked well in explaining exchange rate movements. Especially, the estimated coefficients of money and output variables are consistent with any traditional variants of monetary model.

Caring for cancer patients may create several negative emotions for their family members. Therefore, reducing or alleviating negative feelings are essential in improving mental and physical health of cancer patients’ family members. This research aims to identify the priority levels of the strategies used by cancer patients’ family members to cope with negative emotions, utilizing Analytic Hierarchy. Next, the proposed model is applied in the cases of Vietnamese cancer patients’ family members. Four groups of coping strategies against negative emotions of cancer patients’ family members are used in the model, including: (1) positive emotion-focused coping strategies; (2) negative emotion-focused coping strategies; (3) positive action-focused coping strategies; (4) negative action-focused coping strategies.

Distribution centers selection is a vital task of any company to reduce costs, improve efficiency of transport flows, which yields customer satisfaction. To select the suitable distribution centers, many quantitative and qualitative criteria must be considered in the selection process. Therefore, distribution centers selection can be seen as a multi-criteria decision making (MCDM) problem under vague environment. Single-valued complex neutrosophic sets (SVCNSs), which is generalized of fuzzy sets, complex fuzzy sets and intuitionistic fuzzy sets; can better represent the vague information than the other sets. This paper aims to propose a new the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach based on SVCNSs to select the locations of distribution center. In the proposed TOPSIS approach, the importance weights of criteria, the ratings of alternatives, and their aggregated values are assessed and evaluated using SVCNSs. Then, this paper defines the operational rules of SVCNSs and calculates the aggregated weighted ratings of alternatives. Furthermore, the score, accuracy and certainty function are developed to rank the alternatives. Last, an application to the distribution center location selection is presented to show the advantages of the proposed approach.

Performance assessment of teaching competency plays an important role in educational activities. Previous assessments of lecturers’ performance have failed to distinguish between potential capacity and their teaching effectiveness. To solve this problem, the integrated approach of quantitative assessment and multi-criteria decision-making models has become one of the main trends for assessing the performance of lecturers in multiple dimensions: self, peer-, manager- and student-based evaluation. This paper proposes a novel hierarchical approach, developed by the Technique for Order preference by Similarity to Ideal Solution method in an interval-valued complex neutrosophic set environment, to more accurately and comprehensively understand the evaluation process and fit it into a systematic framework. An application is given to illustrate a practical solution in lecturer’s evaluation. The accuracy of the proposed method is verified by comparing with other methods.

The hybrid vehicle routing problem is an extension of the green vehicle routing problem where vehicles can use different fuels. In this research, a bi-objective hybrid vehicles routing problem is presented and solved bu considering alternative paths, various lengths and reliabilities. The first objective function minimizes overall system costs and fuel consumption and greenhouse gas emissions, whereas the second objective function maximizes the reliability of the entire system with alternative paths and several reliabilites. The proposed model is formulated as mixed-integer nonlinear programming and a bi-objective simulated annealing (MOSA) algorithm along with the e-constraint method is used as solution strategy. The implementation of the proposed method is presented using some numerical instances.

Agricultural food supply chains of different grains such as wheat, rice, and corn include several processes from cropping and harvesting to distribution. Integrating these processes to reduce costs, in addition to providing sufficient supply, are of the major goals of agri-food supply chain management. Rice is an important grain that constitutes an important part of people’s diets throughout the world. FAO predicts that global rice utilization would increase over the next few years. Considering rice's importance, in this paper, a mixed-integer linear mathematical model for designing and planning of rice supply chain is proposed which aims to maximize total profit by integrating different decisions of the rice supply chain including supplier selection, cropping, fertilizing, pest control, harvesting, milling, transportation, and distribution. This model considers different rice varieties and takes into account irrigation water requirements of crops and available water resources. A case study of Iran farmlands in Gilan province is employed to show the applicability and advantages of the proposed model for the rice supply chain. Results indicate that increasing conversion ratio of paddy to rice and reducing labor costs would have a significant impact on the total profit of the supply chain.

Globalization and increasing competition in global markets have forced businesses to provide a high level of service to their customers. Time-sensitive transportation systems which are used in transportation of perishable goods, express mail delivery, and emergency services are playing a very important role in this regard. This paper addresses the problem of uncapacitated multiple allocation p-hub center problem (UMApHCP) which is fundamental in proper functioning of time-sensitive transportation systems. A mixed-integer programming formulation is proposed for the problem and a highly efficient Benders decomposition algorithm is developed for solving it. The proposed algorithm is capable of solving large-scale instances of the problem to optimality in order of seconds.