جستجوی مقالات مرتبط با کلیدواژه "integer programming" در نشریات گروه "مدیریت"

Background and objective:

 Transferring injured people to medical centers is one of the important challenges of providing relief in natural and man-made disasters. Often, due to the damage caused by the disaster, it is not possible to transfer the injured to safe medical centers in the short term. Establishing field hospitals in suitable places is one of the common solutions in these situations. This study aims address the problem of location selection for field hospitals using mathematical modeling and asses how to allocate resources, including medical staff and needed medications by the temporary hospitals.

Method :

This study presents an integer programming model for the location selection problem. To evaluate the proposed model, the real data from Amol City was collected and used as inputs. The optimal solution was determined using GAMS 25.1 optimization software.

Results:

 The calculation results illustrated the best place for the establishment of field hospitals, which is located in Banafsheh Park. It has also been determined that each deployed field hospital should have 60 beds. In addition, the optimal number of medical personnel and relief vehicles for relief operations was determined. The sensitivity analysis has also shown that if any of the hospitals located in Amol is damaged and inactive due to an accident, Hefdeh Shahrivar Square is a suitable place to build a field hospital. 

Conclusion:

 The results of this study can help authorities in Amol city to make the best decisions regarding where to establish field hospitals and how to use the limited available resources during disasters. The main innovation of the presented model also is the location of field hospitals along with considering the active hospitals around the affected areas so that the injured can be transferred to the active hospitals in addition to the constructed field hospitals. In this model, a constraint has been applied to complete the service time, so that the rescue vehicles have a limited time to transport the injured to the rescue centers.

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.

The world's electricity industry has faced numerous challenges, such as rising electricity demand and greenhouse emissions, declining fossil fuel reserves, economic conditions, and rising costs. Such challenges have forced managers to supply energy by replacing fossil fuels with renewable energy sources. The technology advancements and electronic equipment in the consumption sector have increased the need for electricity. Hence, electricity generation has become more significant due to the type of power plant. This study aims to prioritize electricity generation by allocating it to the consumption sector, to reduce greenhouse gas emissions.

Design/methodology/approach:

 In this study, a mathematical has been proposed to determine the amount of electricity production from power plants with different economic, technical, and environmental conditions. Then, the optimal electricity allocated to various sectors (as consumers), such as household, commercial, transportation, industry, and agriculture has been examined. By simulating and proposing a linear programming model, regarding the energy data in 2017, 10 types of the power plant and energy balance have been taken into consideration. Based on a mathematical model and by considering three decision-making variables, while observing the limitations and requirements of the power plant, the amount of electricity generation has been determined. Then, the energy system in the consumption sector has been simulated by causal diagrams using the system dynamics approach.

The lack of fossil fuels and environmental pollution associated with energy development are challenging issues. Fossil fuel production and consumption contribute to global warming and acid rain. Therefore, one solution to protect the environment from the proliferation of energy waste and its consumption is the effective planning of energy systems. Findings indicated the role of proper planning and allocation for energy in the consumption sector, in reducing greenhouse gas emissions.

The lack of comprehensive and accurate data on the application of renewable technologies to generate electricity in Iran is one of the main limitations of the empirical study. One of the limitations of the proposed model is the consideration of renewable and non-renewable sources, simultaneously. Electricity from renewable fuel has also been less noticed.

Practical implications:

 Based on the findings it is concluded that the mathematical model with more comprehensive indicators and the system dynamics model can play a significant role in reducing greenhouse gas emissions. Therefore, the following strategies can be used to reduce greenhouse gas emissions nationwide:- The percentage of electricity generation from renewable energy sources should be increased and the use of fossil resources to generate electricity should be reduced, which is evident from the application of the mathematical function of the model.- Electricity generation from power plants based on the specified priority will significantly reduce greenhouse gas emissions.- According to the calculation of the environmental index, issuing construction permissions for coal and gas power plants should be prevented.- The needs of the domestic and commercial sectors must be met through renewable energy sources.

Originality/value:

 In this study, mathematical planning and dynamic system were used to study technical, economic, and environmental conditions in the reduction of greenhouse gas emissions. Considering the existence of objective functions in the mathematical model and the optimal results obtained from the production of 10 hypothetical power plants in this study, it is implied that the optimal production in solar, wind, combined cycle, heater, water, and natural gas centers has potentials for capacity expansion.

Designing a warehouse entry system, layout, movement and removal of products from the warehouse is critical to maximizing productivity. The use of cross docking has become increasingly important to speed up warehouse operations. Cross docking is a distribution strategy that plays an important role in enhancing the efficiency of distribution networks and reducing customer response times. In loading and unloading products through cross dock warehouses, the products are unloaded by incoming trucks and with a slight delay and sometimes without any delays, they are loaded directly into the outgoing trucks in the temporary storage area. This article, deals with the modeling and design of a cross dock warehouse and the purpose is to determine the allocation of warehouse floor locations to retailers in order to minimize the distance traveled in the warehouse and the vacant space of the warehouse and also maximizing the satisfaction of retailers by considering their shipping priorities. Augmented Epsilon constraint method is used to solve the problem. Finally, ideas and suggestions are presented to develop the model.

In this paper, integrated production and batch delivery scheduling problem for make to order production system and one customer in supply chain has been addressed. One manufacture received n orders from one customer. Orders must be processed by single machine and sent in batches to customer. Sending several jobs as a batch leads to less transportation cost but may increase the cost of tardiness jobs. The objective is determining the production and delivery scheduling so that the related costs is minimized. The problem is strongly NP-hard. In this paper, one new math programming model including Mixed Integer Programming (MIP) model, Ant Colony System (ACS) and Elastic Ant System (EAS) are presented for solving it. In order to evaluate the efficiency of these two methods computational tests based on full factorial experimental design has been conducted. Computational test is performed for evaluation of these methods. The obtained results show that the heuristic algorithm is efficient which has been verified by using. Analysis of variance (ANOVA) technique. The results showed that the ACS is the most efficient method.

Tanavar Co. has had problems in making strategic decisions, due to the lack of a systematic mechanism to manage risk events. Hence to facilitate the enterprise risk management (ERM) process, a decision support system which is able to support decision making at all stages of risk management process has been developed. This research introduces a methodology which supports decision making in the whole process of enterprise risk management and in addition applies multiple attribute decision making (MADM) tools such as weighing method based on eigenvalue approach and TOPSIS method, fuzzy inference system and also integer programming. Applying MADM models for using qualitative, quantitative and sometimes contradictory criteria, and also using experiences and opinions of experts, requires a decision support system. Thus for implementation and validation of recommended model, a software has been developed and applied in Tanavar Co. and specifically in Enghelab sport complex.

One of the most important problems in the system reliability optimization is redundancy allocation problem that has been studied in different system configurations. K-out-of-n structure is a general system configuration and offers enhanced capabilities for analyzing more design problems. Hence, in this paper, the redundancy allocation problem of k-out-of-n systems is studied. In the most previous researches of this problem, a predetermined redundancy strategy is assumed within each subsystem. However, in practice, the choice of redundancy strategy provides more improvement in system reliability. Thus in this paper, the choice of redundancy strategies is considered as decision variables. First the problem is mathematically modeled. Then to overcome the structural complexity of the model, we develop a new linear mathematical formulation to solve the problem with integer programming methods. The proposed algorithm is tested on a well-known test problem that extracted from previous researches. Results show the effectiveness of the proposed algorithm.