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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: HFSs,Flexible manufacturing systems (FMSs),ELECTRE method,Group decision analysis
- چکیده:
- چکیده انگلیسی: A new hesitant fuzzy set (HFS)-ELECTRE for multi-criteria group decision-making (MCGDM) problems is developed in this paper. In real-world applications, the decision makers (DMs)’ opinions are often hesitant for decision problems; thus, considering the exact data is difficult. To address the issue, the DMs’ judgments can be expressed as linguistic variables that are converted into the HFSs, considered as inputs in the ELECTRE method. Meanwhile, an appropriate tool among the fuzzy sets theory and their extensions is the HFSs since the DMs can assign their judgments for an alternative under the evaluation criteria by some membership degrees under a set to decrease the errors. Introduced hesitant fuzzy ELECTRE (HF-ELECTRE) method is elaborated based on the risk preference of each DM with assigning some degrees. Moreover, the weight of each DM is computed and implemented in the proposed procedure to reduce judgments’ errors. Then, a new discordance HF index is provided. Pair-wise comparisons are used for outranking relations regarding HF information. Finally, the validation and verification of the proposed HF-ELECTRE method are demonstrated in a practical example of FMSs.
- انتشار مقاله: 12-07-1395
- نویسندگان: Seyed Meysam Mousavi,Hosein Gitinavard,Behnam Vahdani
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Mega projects,interval-valued fuzzy sets,Earned value analysis,interval-valued earned value indices
- چکیده:
- چکیده انگلیسی: The earned value technique is a crucial and important technique in analysis and control the performance and progress of mega projects by integrating three elements of them, i.e., time, cost and scope. This paper proposes a new version of earned value analysis (EVA) to handle uncertainty in mega projects under interval-valued fuzzy (IVF)-environment. Considering that uncertainty is very common in mega projects’ activities, the proposed IVF-EVA model is very useful and applicable in evaluating the progress of projects. In this paper, analyzing earned value indices and calculating them with linguistic terms have been discussed. They are then converted into interval-valued fuzzy numbers (IVFNs) for the evaluations. Finally, an application example from the recent literature is presented and steps of the proposed IVF-EVA are elaborated.
- انتشار مقاله: 12-09-1394
- نویسندگان: N Moradi,Seyed Meysam Mousavi,Behnam Vahdani
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Hesitant fuzzy sets,Last aggregation,Group decision-making,Compromise ranking,Euclidean–Hausdorff distance measure,Facility location selection problem
- چکیده:
- چکیده انگلیسی: Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromise ranking is more capable and powerful than the classical compromise ranking. This research extends a new hierarchical group compromise ranking methodology under a hesitant fuzzy (HF)environment to handle uncertainty, in which for the margin of error, the DMs could assign the opinions in several membership degrees for an element. The hesitant fuzzy set (HFS)is taken into account for the process of the proposed hierarchical group compromise ranking methodology, namely HFHG-CR, and for avoiding the data loss, the DMs’ opinions with risk preferences are considered for each step separately. Also, the Euclidean–Hausdorff distance measure is utilized in a new proposed index for calculating the average group score, worst group score and compromise measure regarding each DM. A new ranking index is presented for final compromise solution for the evaluation. Proposed HFHG-CR methodology is applied to a practical example for a facility location selection problem, i.e. cross-dock location problem, to show the validation and application.
- انتشار مقاله: 17-01-1394
- نویسندگان: Seyed Meysam Mousavi,Hossein Gitinavard,Behnam Vahdani,Nazanin Foroozesh
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Cost forecasting,Project cash flow,Fuzzy project scheduling,Assessment method,Interval-valued fuzzy sets (IVFSs)
- چکیده:
- چکیده انگلیسی: Effective project management requires reliable knowledge of cash required in different stages of project life cycle. Getting this knowledge is highly dependent on sophisticated consideration of project environment. Nature of projects and their environments are associated with uncertain conditions. In this paper, a new project cash flow assessment method based on project scheduling is proposed to foresee projects' cash flow in their different stages. Interval-valued fuzzy sets (IVFSs) are applied to address the uncertainty of activity durations and costs. First, an IVF-project scheduling method is proposed to calculate early start time and early finish time of activities under IVF-environment and based on that, a new method of cash flow assessment is introduced under IVF-environment. For the purpose of illustration, the proposed method is implemented to generate cash flow of main activities of a large-scale project. The results show the flexibility of presented assessment method in expressing uncertainty, in addition to its capability in risk evaluation. Furthermore, using alpha-cuts to address different levels of uncertainty and risk provides a comprehensive insight of the cash required in different stages of project life cycle under different levels of risk and uncertainty. Finally, the results are discussed and the proposed method is believed to be useful in the project evaluation.
- انتشار مقاله: 14-07-1394
- نویسندگان: Vahid Mohagheghi,SEYED Meysam Mousavi,Behnam Vahdani
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: TOPSIS,MCDM,block angular structure,MODM,Multi-Objective Large-Scale Linear Programming (MOLSLP)
- چکیده:
- چکیده انگلیسی: This paper proposes a compromise model, based on the technique for order preference through similarity ideal solution (TOPSIS) methodology, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. This compromise programming method is based on the assumption that the optimal alternative is closer to fuzzy positive ideal solution (FPIS) and at the same time, farther from fuzzy negative ideal solution (FNIS).An aggregating function that is developed from LP- metric is based on the particular measure of ‘‘closeness” to the ‘‘ideal” solution.An efficient distance measurement is utilized to calculate positive and negative ideal solutions. The solution process is as follows: first, the decomposition algorithm is used to divide the large-dimensional objective space into a two-dimensional space. A multi-objective identical crisp linear programming is derived from the fuzzy linear model for solving the problem. Then, a single-objective large-scale linear programming problem is solved to find the optimal solution. Finally, to illustrate the proposed method, an illustrative example is provided.
- انتشار مقاله: 11-06-1390
- نویسندگان: Behnam Vahdani,Meghdad Salimi,Behrouz Afshar Najafi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Artificial Neural Networks,Construction projects,Time prediction,locally linear neuro-fuzzy model
- چکیده:
- چکیده انگلیسی: This paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. The output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (LLNF) model, is useful for assessing a project status at different time horizons. Being trained by a locally linear model tree (LOLIMOT) learning algorithm, the model is intended for use by members of the project team in performing the time control of projects in the construction industry. The present paper addresses the effects of different factors on the project time and schedule by using both fuzzy sets theory (FST) and artificial neural networks (ANNs) in a construction project in Iran. The construction project is investigated to demonstrate the use and capabilities of the proposed model to see how it allows users and experts to actively interact and, consequently, make use of their own experience and knowledge in the estimation process. The proposed model is also compared to the well-known intelligent model (i.e., BPNN) to illustrate its performance in the construction industry.
- انتشار مقاله: 23-01-1390
- نویسندگان: Behnam Vahdani,Seyed Meysam Mousavi,Morteza Mousakhani,Hassan Hashemi
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: fuzzy sets,Shortest path problem,Single criterion networks,Multiple criteria networks,Ideal fuzzy sets
- چکیده:
- چکیده انگلیسی: A shortest path problem is a practical issue in networks for real-world situations. This paper addresses the fuzzy shortest path (FSP) problem to obtain the best fuzzy path among fuzzy paths sets. For this purpose, a new efficient algorithm is introduced based on a new definition of ideal fuzzy sets (IFSs) in order to determine the fuzzy shortest path. Moreover, this algorithm is developed for a fuzzy network problem including three criteria, namely time, cost and quality risk. Several numerical examples are provided and experimental results are then compared against the fuzzy minimum algorithm with reference to the multi-labeling algorithm based on the similarity degree in order to demonstrate the suitability of the proposed algorithm. The computational results and statistical analyses indicate that the proposed algorithm performs well compared to the fuzzy minimum algorithm.
- انتشار مقاله: 15-12-1390
- نویسندگان: Sadollah Ebrahimnejad,Seyed Meysam Mousavi,Behnam Vahdani
- مشاهده
- جایگاه : پژوهشی
- مجله: Journal of Optimization in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Supply Chain Management,Facility location,Two-stage optimization,Multiple uncertainties
- چکیده:
- چکیده انگلیسی: The development of optimization and mathematical models for closed loop supply chain (CLSC) design has attracted considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of the developed tools. The aim of this paper, therefore, is to propose a new mathematical model for designing a CLSC network that integrates the network design decisions in both forward and reverse supply chain networks. Moreover, another objective of this research is to introduce an inexact-fuzzy-stochastic solution methodology to deal with various uncertainties in the proposed model. Computational experiments are provided to demonstrate the applicability of the proposed model in the CLSC network design.
- انتشار مقاله: 11-09-1390
- نویسندگان: Behnam Vahdani,Mani Sharifi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Robust optimization,uncertainty,Capacity planning,Closed-Loop network,Supply chain design
- چکیده:
- چکیده انگلیسی: In this paper, firstly by using a mixed linear programming a new model of locating facilities with limited capacity is presented to design a closed-loop supply chain in a multi-product and multi-period mode. Then, using a robust optimization approach, the proposed model decreases in non-deterministic expansion. The results show that the proposed model can handle facility capacity in a closed loop logistics network. In addition, the results showed that the cost and time of test problems for the robust model is higher than the deterministic model.
- انتشار مقاله: 05-05-1394
- نویسندگان: Siamak Jebreilzade,Behnam Vahdani,Seyed Meysam Mousavi
- مشاهده
- جایگاه : پژوهشی
- مجله: Advances in Industrial Engineering
- نوع مقاله: Journal Article
- کلمات کلیدی: Project Portfolio Selection,Construction projects,Mathematical Programming,Sustainable Development,Type-2 fuzzy sets
- چکیده:
- چکیده انگلیسی: Choosing the right set of projects is the first step of project oriented firms in strategic project portfolio management. Since economic growth depends on environmental and social issues, sustainable development has been an essential part of firms' plans to keep their competitive advantage. Moreover, market conditions, fast worldwide changes and other similar issues have given these issue ever-growing uncertain elements. As a result, this paper provides a method of sustainable construction-project portfolio selection under interval-valued type-2 fuzzy sets. This method consists of two main parts. The first level evaluates the proposed projects and omits the unsuitable ones. Then, in the second level, the portfolio is selected by means of mathematical programming. Eventually, to display applicability of the method, an application example is presented and solved.
- انتشار مقاله: 30-06-1394
- نویسندگان: Vahid Mohagheghi,Seyed Meysam Mousavi,Behnam Vahdani
- مشاهده