احمد یوسفی هنومرور

The proposed model is a time-cost-quality trade-off model with three objective functions: minimizing project completion time, minimizing total project cost, and maximizing total quality of activities in a PERT network with multi-mode activities.

After presenting the appropriate mathematical model, based on the design of the experiments, the possible levels of each decision variable were determined. Then, using the simulation process, random values ​​of decision variables and response variables were obtained each time, and by using neural networks, we established a neural network model. To solve this model, two algorithms NSGA-II and MOPSO were used.

To evaluate the efficiency of the model, the designed model was implemented in the maintenance department of Abtin Ardakan Steel Company. According to the results, it is found that the NSGA-II algorithm has better performance than the MOPSO algorithm.

In this paper, a model was presented that by eliminating unrealistic assumptions and taking into account the realities of the project is closer to reality than the models presented in this field and has more application in practice.

Time, cost and quality are important goals of any project. Todays, the demand of project stakeholders to reduce total project costs has increased simultaneously time reduction and augment in quality of the project. This leads researchers to develop models that add quality factor to previous models of cost-time balance. In this paper, a time-cost-quality trade -off model with three objective functions includes minimizing project termination, minimizing total project cost and maximizing total quality of activities in a multi-modal PERT network was investigated. After presenting the appropriate mathematical model, a decision was made on the basis of a test plan of possible levels for each variable. Then, using the simulation process, random values of decision variables and response variables were implemented at each time, and we developed a neural network model using artificial neural networks. To solve this model, since the problem is in the NP-hard category, two multi-objective meta-heuristic algorithms NSGA-II and MOPSO were used. To determine the performance of the proposed model, the problem was tested on a small, medium and large-scale PERT network. The parameters of these two meta-heuristic algorithms were adjusted by Taguchi method and the results were based on the parameters set showed that the NSGA-II algorithm performs better than the MOPSO algorithm.

In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have been considered. The main innovation of this research is to consider the failure and repair rates of components with non-exponential distribution function in the process of optimization. The parameters affecting the under-study system in this paper make it impossible to calculate the availability using mathematical relations. Therefore, the present study has used simulation method to calculate system availability. Since the simulation has no optimization capability, this research tries to represent the results of the simulation as a mathematical function, which explains the way decision variables affect the system's availability. Further, due to the high degree of difficulty of developed mathematical function, the genetic metaheuristic algorithm was used to solve it. Finally, the efficiency of the genetic algorithm was measured against particle swarm algorithm and simulated annealing algorithm. To compare fairly, the parameters affecting the algorithms are adjusted using the Taguchi method and the algorithms are in their best practice. The computational results prove the high ability of the genetic algorithm in optimizing the concerned problem.

Evaluation and measuring performance causes smart system and motivatedindividuals to showthe right behavior, and this is a main part in designing and implementation of organizational policies. Evaluation performance describesproductivity activities and organizationplans. Identifying performance indicators to guide the organization toward long-term goals is vital in acomplexbusiness condition. In this study the limitations of performance metrics and strategies assessedby the Balanced Score card and Analytical Process Network and Game theory as means to increase the effectiveness. As the case of the study, Tehran Municipal Region 4 shows Quantification of factors affecting success of an organization using Paired comparison preferences and affiliations of these factors using Analytical Process Network.Adopting this model helps organizations regarding the issues discussed. In addition, with the approach of group games in game theory, any aspect of the Balanced Score Card considered as a player and value of each player's shapedcoalition was determined. Finally, with regard to the values obtained, the best strategy combination selected and suggested.

This research focuses on the integration of lean, agile, resilient and green paradigms in the supply chain and the constraints of SWOT analysis, in order to improve the performance of the supply chain. First, multi-criteria decision making techniques were used. Then, SWARA method was used to weigh the criteria of the LARG supply chain and the gray ARAS method was used to prioritize the strategies. At various levels of SWOT analysis, strengths, weaknesses, opportunities and threats were identified and appropriate strategy was opted. Finally, in order to determine the optimal combination of strategies, the fuzzy Shaply value and game theory were used. In this paper, the results showed the most important criteria are business waste, quality and cost. To determine the optimal combination, eight strategies were selected at different levels of strength, weakness, opportunity, and threat from SWOT analysis. According to the results of the research, the optimal combination of SO2ST2WO2WT1 strategy was proposed, which included strategies for the existence of an integrated networking for the production, transfer, reduction of technical and non-technical wastes in distribution network and purchasing of electricity by private companies.

Organizations to remain competitive and dynamic business environment require a correct analysis of the internal situation and their own environment In order to obtain a variety of appropriate strategies. One of the most widely used management tools in the analysis and strategic planning is SWOT that formulated The strategies based on an analysis of internal and external factors. However, SWOT analysis along with advantages, it also has some limitations, such as assuming independence between strategic and ranking strategic factors and strategies. This paper covers SWOT analysis limits by combining it with the fuzzy net present value and is fuzzy Shaply value and provides a conceptual framework of combination these three tools. Finally The conceptual framework also implements in a power Co and determined the optimal combination strategy of this organization.