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Showing 9 results for Decision-Making

M.b Aryanezhad , A. Roghanian ,
Volume 19, Issue 1 (3-2008)
Abstract

Abstract: Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problems are concerned with synchronizing and optimizing multiple activities involved in the enterprise, from the start of the process, such as procurement of the raw materials, through a series of process operations, to the end, such as distribution of the final product to customers.  Enterprise-wide supply chain planning problems naturally exhibit a multi-level decision network structure, where for example, one level may correspond to a local plant control/scheduling/planning problem and another level to a corresponding plant-wide planning/network problem. Such a multi-level decision network structure can be mathematically represented by using “multi-level programming” principles. This paper studies a “bi-level linear multi-objective decision making” model in with “interval” parameters and presents a solution method for solving it this method uses the concepts of tolerance membership function and multi-objective multi-level optimization when all parameters are imprecise and interval .

  


M.b. Aryanezhad , E. M.b.aryanezhad & E.roghanian ,
Volume 19, Issue 1 (3-2008)
Abstract

  Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problems are concerned with synchronizing and optimizing multiple activities involved in the enterprise, from the start of the process, such as procurement of the raw materials, through a series of process operations, to the end, such as distribution of the final product to customers.

  Enterprise-wide supply chain planning problems naturally exhibit a multi-level decision network structure, where for example, one level may correspond to a local plant control/scheduling/planning problem and another level to a corresponding plant-wide planning/network problem. Such a multi-level decision network structure can be mathematically represented by using “multi-level programming” principles. This paper studies a “bi-level linear multi-objective decision making” model in with “interval” parameters and presents a solution method for solving it this method uses the concepts of tolerance membership function and multi-objective multi-level optimization when all parameters are imprecise and interval .

 


Mahdi Karbasian, Mohammad Farahmand, Mohammad Ziaei,
Volume 26, Issue 2 (7-2015)
Abstract

This research aims at presenting a consolidated model of data envelopment analysis (DEA) technique and value engineering to select the best manufacturing methods for gate valve covers and ranking the methods using TOPSIS.To do so, efficiency evaluation indices were selected based on the value engineering approach and different manufacturing methods were evaluated using DEA technique.Finally, effective methods were ranked based on TOPSIS. Accordingly, 48 different methods were identified for manufacturing the part. The DEA results showed that only 12 methods have complete efficiency. Meanwhile manufacturing method No. 32 (A216 WCB casting purchased from Chinese market as the raw material, machining by CNC+NC and drilling by radial drill) was ranked the first.Major limitations of the research include time limitations, place limitation, lack of access to the standards adaptability index in different machining and drilling methods, limitation on evaluating all parts of a product, limitation on a technique evaluating efficiency and ranking, and mere satisfying with superior indices in each factor of value engineering. Most previous studies only evaluated efficiency of manufacturing methods based on a single approach.By applying value engineering, which is in fact a combination of three approaches (including quality approach, functional, and cost approaches), the present research provided a far more comprehensive model to evaluate manufacturing methods in industrial.

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Ali Bonyadi Naeini, Barat Mojaradi, Mehdi Zamani, V.k. Chawla,
Volume 30, Issue 3 (9-2019)
Abstract

The frequency of chronic diseases such as cardiovascular diseases has significantly increased in recent years. This study is a developmental research which is categorized as descriptive-survey in terms of data collection method. The aim of this study is to prioritize 22 districts of Tehran for the purpose of prevention from cardiovascular diseases. In the present study, after extraction of the effective factors on the prevalence of cardiovascular diseases from previous studies, the weight of each factor with their specific data for each 22 districts of Tehran (collected from relevant organizations) is obtained using two levels of Fuzzy Delphi method and one level of fuzzy best-worst method, for confirming or denying factors and weighting them based on the opinion of 25 cardiologists, respectively, and transferred to Arc GIS software for prioritizing 22 districts of Tehran.Using a combination of fuzzy best-worst method, which is one of the newest methods for making multi-criteria decision, and GIS, for weighting parameters and prioritizing 22 districts of Tehran, gives an acceptable worth to the present study.Our results-after classification, drawing, and combination of maps- indicated that the 8th district (except a little part in the west) is the best district, and 16th and 19th districts (approximately whole district) are in the last priority for prevention of cardiovascular diseases. Other districts respectively placed in the second to 21th places.
Badr Dakkak, El Hassan Irhirane, Ahmed Bounit,
Volume 32, Issue 4 (12-2021)
Abstract

Overall Equipment Effectiveness (OEE) is a very powerful indicator for the performance evaluation of a manufacturing organization. However, determining the OEE target remains subjective and it’s usually based on the decision of concerned managers. In this paper, we tested the OEE target determination model based on the measured OEE. Such a method is based on the fuzzy logic principle and on two other decision-making support methods. To do this, we began with a literature review on OEE and its constituents. Then, a detailed description of the research methodology and the proposed model is provided. Thus, a case study in a manufacturing agri-food organization was conducted to test the proposed model and validate the obtained results.
Liudmyla Bezuhla, Iryna Koshkalda, Iryna Perevozova, Serhii Kasian, Nataliia Hrechanyk,
Volume 33, Issue 1 (3-2022)
Abstract

Tourists are getting more aware of the environment. To determine the effectiveness of eco-tourism infrastructure management, the motivation and segmentation of demand for eco-tourism have been analysed using functional theory as a guide. The empirical analysis was conducted in the Dnipro, Zaporizhzhia, and Kherson regions. 382 surveys were obtained by random sampling. To make the data analysis, factor analysis and non-hierarchical segmentation were performed. The results indicate that there are several eco-tourism motivational aspects including self-development, interpersonal relationships, defence functions, building personal relationships, reward, and appreciation from nature. Three different segments of eco-tourists were also identified based on their motives related to nature, reward, and escape. Characteristics of different segments were also specified. This study will help government agencies and private companies improve their travel content and develop more effective marketing plans.
The research has shown that in most cases, the success of any project is in cooperation between NGOs, locals, authorities, and the private sector. The optimal level of local participation is determined by the specifics and scale of each project, which may focus on individual villages or several communities that experience any impact of tourism.
The economic essence of the concept of tourism motivation has been improved, which is defined as a set of needs that affect a person in the process of participation in tourism activities and are a central factor in the decision-making process. Studying the most important motivations of eco-tourists in the region, three groups of motives have been identified: cultural and educational activities, proximity to nature, health and rehabilitation measures.
Hamza Samouche, Abdellah El Barkany, Ahmed Elkhalfi,
Volume 34, Issue 2 (6-2023)
Abstract

Sales and operations planning (S&OP) is considered as an important tool at the planning strategic level. Its models vary depending on industries. The Asian model is known to be very developed. Having several parameters, the Asian model proves to be an effective tool, precisely for the study of capacity. However, after several searches made in various databases, we did not find any concrete model actually used in industry and whose parameters are presented and which defines the analysis logic to better align supply and demand. In this article, we will carry out various simulations on the basis of the data of a model of sales and operations planning used in a wire harnesses factory, in order to explain the decision-making process during S&OP meetings. The parameters of the model and the various constraints that were facing the sales and operations planning team are presented and discussed as well as the financial consequences of certain decisions. As a result of this study, we can notice that S&OP is indeed a powerful tool that makes it possible to detect in advance the various constraints whose resolution concludes in an optimal alignment between customer demand and factory capacity.
 
Amin Amini, Alireza Alinezhad, Davood Gharakhani,
Volume 35, Issue 2 (6-2024)
Abstract

The selection of a sustainable supplier is a multi-criteria decision-making issue that covers a range of criteria (quantitative-qualitative). Selecting the most eco-friendly suppliers requires balancing tangible and intangible elements that may be out of sync. The problem gets more complicated when volume discounts are taken into account, as the buyer needs to decide between two issues: 1) What are the best sustainable suppliers? 2) Which amount needs to be bought from each of the selected eco-friendly suppliers? In current study a combined attitude of best-worst method (BWM) ameliorated via multi-objective mixed integer programming (MOMIP) and rough sets theory is developed. The aim of this work is to contemporaneously ascertain the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products with multiple criteria and with capacity constraints of suppliers and the number of suppliers to employ. In this situation, price reductions are offered by suppliers based on add up commerce volume, not on the amount or assortment of items acquired from them. Finally, a solution approach is proposed to solve the multi-objective model, and the model is demonstrated using a case study in Iran Khodro Company (IKCO). The results indicate that ISACO is the most sustainable supplier and the most orders are assigned to this supplier.

Sina Nayeri, Mahla Zhain Vamarzani, Zeinab Asadi, Zeinab Sazvar, Nikbakhsh Javadian,
Volume 35, Issue 3 (9-2024)
Abstract

This study focuses on evaluating potential raw material providers (RMPs) as one of the critical tasks of the logistics managers. In this regard, the literature showed that the simultaneous consideration of resilience, digitalization, and circular economy in the RMP selection problem (RMPSP) has been ignored by previous studies. Therefore, to cover the mentioned gap, this research attempts to study the RMPSP by considering other crucial concepts namely resilience and Circular Economy (CE). For this purpose, by considering a real-world case study in the steel industry, the current work first specifies the indicators of the research problem. Then, the indicators’ weights are measured using the stochastic Best-Worst Method (BWM). In the next step, the RMPs are prioritized by developing a novel approach called the stochastic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In general, the main objective of this study is to evaluate the performance of the RMPs in the steel industry based on the CE, resilience, and digitalization aspects. According to the achieved results, “Reliability”, “Price”, “Quality”, “Reverse logistics and Waste management”, “Information systems usage”, and “Restorative Capacity”, are identified as the most desirable indicators. Moreover, the results confirm the effectiveness and validation of the developed method.


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