Modern Research in Decision Making

Abstract The problem of course timetabling problem deals with the creation of a timetable, the purpose of which is to assign courses to different time periods in the week and to determine an arrangement of courses that is acceptable and feasible for teachers, students, and higher education institutions while complying with the educational regulations.
In this work, we attempted to consider a scheduling problem in which the compactness of the curriculum, the distribution of the course schedule in the time frame, the preferences of the professors, the minimum number of working days, the maximum capacity, and the sustainability of the classes (with the goal of minimizing the daily commute of students between classes) should be considered. To model the problem, we considered a mathematical programming problem of nonlinear integer type with large dimensions. The solution of the mathematical model with using the software GAMS and the results of course planning for the second semester of the master's program in applied mathematics at Iran University of Science and Technology are reported at the end.

Abstract The evaluation information mainly relies on expert’s subjective judgment, which is imprecise and uncertain, and this issue is also true in the supplier selection. In order to improve and achieve reliable results, this study provides a systematic framework for selecting suppliers based on sustainability dimensions in which a hybrid fuzzy- rough AHP-WASPAS approach is proposed for sustainable supplier selection. The effectiveness of the proposed methodology is illustrated through its application in Kurdistan Gas Company supplier selection. First, the sustainable supplier selection criteria are determined by reviewing previous research. After screening the sustainable supplier selection criteria with the fuzzy Delphi method, AHP based on fuzzy rough numbers is used to determine the weights of criteria. Finally, a developed version of Waspas method, namely the Waspas method based on rough-fuzzy numbers, is introduced which can be applied in the environment of vague and uncertain decision making. This proposed approach is used to rank sustainable suppliers of Kurdistan Gas Company.

Abstract Nowadays, the stock market plays an important role in the economy of different countries. The abundance of data in the stock market and the need for fast and correct data processing and making appropriate decisions have made the use of computers inevitable. In this article, using deep reinforcement learning, a model is designed to present the duties of a trader in the Iranian stock market with regard to liquidated shares. In the first step, the history of stock prices along with the indicators based on it are given as inputs to the convolutional neural network. In the next step, in order to calculate the matching rate of the convolution output with the expected output, the sum of squared error cost function is used, which, in turn, is minimized in the optimization process. Since the data in the Iranian stock market is limited, using the convolution model instead of the Q table in the deep reinforcement model prevents the over fitting of the model. In order to evaluate the model, the data of Tehran Stock Exchange was used in the period of 1390 to 1400. The performance of the proposed method was compared with the buy and hold strategy. The results show, in some cases, the profit from the proposed method in contrast with buy and hold strategy is 21% and -7%, respectively.

Abstract Facility location whit taking account the competition is a critical component of strategic planning. The location affects the competitiveness and market share of a new entry firms, in long term life. In order to develop a model with more realistic characters, demand is supposed elastic. In this research, demand is defaulted with the help of an exponential function. In this paper a competitive facility location model whit two competitors which produce a commodity with elastic demand is developed The problem is modeled in the form of a location-price game. A bi-level model is developed to investigate the location and price, in location-pricing models, the location decision should come before the pricing game. From the second level and the use of Nash equilibrium, equilibrium will be obtained. In this paper, probabilistic costumer behavior whit the help of exponential function is modeled. A metaheuristic based on tabu search and Simulated annealing algorithm are proposed to search the optimal location-price solution of the model. The analysis shows that price game is more intense when incomes of consumers are lower or there are more substitution products.

Abstract One of the most important issues in the field of sustainable supply chain that affects the environment is the amount of contamination generated by the supply chain facilities. Failure to pay attention to this issue will have many economic, social and environmental consequences. Therefore, this research addresses this issue. In this study, a novel model for design of sustainable supply chain network is proposed where only environmentally friendly facilities can operate and others should be repaired or renovated. Furthermore, in order to increase the development and improve the living and social conditions of the people, in the proposed model, location of manufacturers is selected from among less developed regions with greater growth potential. To calculate the growth potential of the regions, criteria such as proximity to neighboring countries with higher GDP, unemployment rate, number of mines, etc. are considered and integrated with multi-criteria decision-making techniques. The methodology of this research is that first, the scores are calculated for each region by the decision-making methods, and then the problem including these scores is optimized. The modeling includes two stages of calculating the growth potential score of each region with multi-criteria decision-making techniques and then formulating a sustainable supply chain network problem. Finally, performance of the proposed model and reduction of environmental impacts to improve the sustainability of logistics systems are investigated and illustrated in a case study. In order to validate the model, several different sensitivity analyzes are presented. The results of computational analysis show efficiency and effectiveness of the model.

Abstract With the increasing competition between manufacturers to respond to customers' requirements, the production planning processes in the form of supply chains has become more complex. On the one hand, manufacturers have to produce at the lowest cost in order to create a competitive advantage. On the other hand, environmental requirements and attention to sustainable production have caused more attention to energy consumption in production systems. In this research, for the first time, the green hybrid flow shop scheduling problem is investigated with considering batch delivery system. For this purpose, a bi-objective integer linear programming model is presented. The first goal of the problem is to minimize the total cost related to the total jobs completion times and the costs of dispatching the batches. The second goal is to minimize energy consumption. The mathematical model is converted to a single objective model using Ɛ-constraint method and a number of random instances are evaluated and comprehensively analyzed with its help, and the effect of paying attention to energy consumption on the scheduling of orders is presented. Also, due to the NP-hardness of the problem, an MOTLBO algorithm has been adopted to solve large size instances.

Abstract The purpose of this research is a systematic review of existing articles with the historical approach in decision-making in strategic change, in the period from 1990 to January 21, 2021 were reviewed and finally, by applying the research protocol, 84 articles were selected that determined the role of organizational history dimensions under the five themes: "historical structure of decision-making power", "stages of the organizational life cycle", "identity-making documents", "organizational experience in the decision to change" and "organizational culture"; In this analysis, the role of "historical structure of decision-making power" has the components of "CEO succession process", "CEO independence and support for change", "extent of human and social capital of the board of directors", "depth of human and social capital of the board of directors", "power board of directors" and "supervisory and governance mechanisms", the role of "stages of the organizational life cycle" has the components of "small size", "large size providing change resources", "advantage due to scale", "young age of the organization" and " The stage of introduction and maturity in the life cycle", the role of "historical identity and organizational experience" has the components of "identity vacuum due to change", "formal and informal narratives and orientations encouraging change", "successful change experience", "organization's habit of change" and "the need for change in official speeches, reports and organizational news" and finally the role of "organizational culture" has the components of "predominance of change discourse", "organizational forgetting", "ceremonies, customs, stories and legends in the organization" and It is a "supportive organizational atmosphere".