Technique For Order Performance By Similarity To Idea Solution Research Articles

AHP-TOPSIS: Multi-Criteria Decision Making Method With Hierarchical Weighting to Determine Priorities for Leak Work Drinking Water Pipe

This research aims to develop an effective multi-criteria decision making method by paying attention to the validity of the criteria weighting. In previous research, the TOPSIS method was applied to the problem of determining priorities for repairing drinking water pipe leaks by paying attention to four (4) criteria, namely the duration of the complaint, the size of the leak, the leak point, and the distance from the leak point to the location of the officer handling the leak.. The research results show that the TOPSIS method has a simple concept and is able to provide priority recommendations for the order of work based on consumer complaints. However, in this research the results of decision making were considered not optimal because the TOPSIS method for calculating criteria weights did not yet have a hierarchical mediator that guaranteed the validity of the criteria weightings. Therefore, this research tries to combine two methods (AHP-TOPSIS), namely Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Idea Solution (TOPSIS). AHP is a Multi Criteria Decision Making (MADM) method that can be used to determine criteria weights hierarchically, with a smooth order of levels and considering the relationship between criteria. In this research, AHP was used to obtain criteria weights and TOPSIS to rank priorities for work on drinking water pipe leaks. The research results show that AHP-TOPSIS can produce a more effective and valid rating to help solve the problem of determining priorities for working on drinking water pipe leaks. This solution is the best decision where work priorities are selected based on criteria that are in accordance with service priorities.

Pro NDN : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking

Named data networking (NDN), as a specific architecture design of information-centric networking (ICN), has quickly became a promising candidate for future Internet architecture, where communications are driven by data names instead of IP addresses. To realize the NDN communication paradigm in the future Internet, two important features, stateful forwarding and in-network caching, have been proposed to cope with drawbacks of host-based communication protocols. The stateful forwarding is designed to maintain the state of pending Interest packets to guide Data packets back to requesting consumers, while the in-network caching is used to reduce both network traffic and data access delay to improve the overall performance of data access. However, the conventional stateful forwarding approach is not adaptive and responsive to diverse network conditions because it fails to consider multiple network metrics to make Interest forwarding decision. In addition, the default in-network caching strategy relies on storing each received Data packet regardless of various caching constraints and criteria, which causes the routers in the vicinity of data producers to suffer from excessive caching overhead. In this paper, we propose the Pro NDN , a novel stateful forwarding and in-network caching strategy for NDN networks. The Pro NDN consists of multicriteria decision-making (MCDM) based interest forwarding and cooperative data caching. The basic idea of the MCDM-based interest forwarding is to employ Technique for Order Performance by Similarity to Idea Solution (TOPSIS) to dynamically evaluate outgoing interface alternatives based on multiple network metrics and objectively select an optimal outgoing interface to forward the Interest packet. In addition, the cooperative data caching consists of two schemes: CacheData, which caches the data, and CacheFace, which caches the outgoing interface. We conduct extensive simulation experiments for performance evaluation and comparison with prior schemes. The simulation results show that the Pro NDN can improve Interest satisfaction ratio and Interest satisfaction latency as well as reduce hop count and Content Store utilization ratio.

An Integrated Hybrid MCDM Approach for Vendor Selection Problem (Case Study: Iran Khodro)

Vendor selection is an important issue in most company based on many criteria that includes ambiguous or uncertain data. Therefore in the study, it is essential that fuzzy approach is employed for coping with the uncertainty and achieving more accurate results. In other hand, the relationships between criteria and sub-criteria are complex; for encompassing the complexity, most conventional decision models cannot help us explain the interrelationships among the criteria. In this paper, a hybrid multi-criteria decision making (MCDM) technique is proposed to determine the structural relationships and the interrelationships among all the evaluation’s dimensions based the Analytic Network Process (ANP) method determining appropriate weightings to each sub-criterion. Then alternatives priority should be determined which can aid the decision making. For the purpose, The TOPSIS (technique for order performance by similarity to idea solution) is used to rank all competing alternatives in terms of their overall performances. In MCDM studies and research, applying TOPSIS in ranking alternatives has recently been customary because of its advantages. In the end, a case study of an Iranian company, in automotive industry, is demonstrated to illustrate the proposed model can improve solving of vendor selection problem.

A framework for selection of logistics outsourcing partner in uncertain environment using TOPSIS

With globalisation and liberalisation, the markets are turning competitive. The key area for industry now is to make the product available to the end customer in time, without damage and loss due to over or under stocking. Hence, logistics is seen as an important area where industries can cut costs and improve their customer service quality. The latest trend is to outsource logistics activities to allow the outsourcing company to concentrate on the core competence, improve the service and reduce the capital cost. In this paper, a framework is proposed to select the most suitable outside Logistics Company (3PL) using fuzzy Delphi method to shortlist the most important criteria and fuzzy technique for order performance by similarity to idea solution (TOPSIS) to choose the best 3PL by finding the closeness to the positive ideal solution. The weights to the opinion of decision-makers (DMs) are assigned according to their qualification, experience and designation. The integrated approach of fuzzy Delphi and fuzzy TOPSIS enhances the accuracy of the result and proves to be helpful for the DMs. A case study is conducted in an automobile company in North India to select the best suitable 3PL service providers to demonstrate the proposed methodology.

Vendor Evaluation Using Multi Criteria Decision Making Technique

A supply chain is a network of departments, which is involved in the manufacture of a product from the procurement of raw materials to the distribution of the final products to the customer. The term supply chain is already invoked effervescence among the managerial community. The purchasing function has gained importance in the supply chain management due to factors such as globalization, increased value addition in supply and accelerated technology change. A key and perhaps the most important process of the purchasing function is the efficient selection of suppliers, because it brings significant savings for the organization. In general, the supplier selection criteria most commonly used by the industries are quality, delivery and price. Also, depending on the corporate environment of the industries, the importance of the performance measure can vary. In this work a versatile technique namely multi criteria decision making (MCDM) technique which involves the analytical network process (ANP) and technique for order performance by similarity to idea solution (TOPSIS) method has been used to select the best vendor. Analytical Network Process and TOPSIS method are powerful decision making processes which help people to set priorities on parameters that are to be considered by reducing complex decision to a series of one-to-one comparisons, thereby synthesizing the result When any vendor for a particular item make changes for the parameters like price, quality etc to improve his performance or has improved abilities in managing supply chain by providing better delivery to his customer, the whole hierarchy process for arriving the ranking of vendors is to be performed again for finding out the best vendor. Now it is felt that a standard automated procedure which could perform the above processing task is essential. So, standard software was developed in a suitable platform such as VB, .NET and MS access that could meet the current requirement. This package can be executed several numbers of times with changing input parameters values thus serving the purpose.

A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems

This study described a hybrid model for supporting the personnel selection process in manufacturing systems. Personnel selection is a very important issue for an effective manufacturing system, since the improper personnel might cause many problems affecting productivity, precision, flexibility and quality of the products negatively. On the other hand, selecting the best personnel among many alternatives is a multi-criteria decision making (MCDM) problem. In this study, a hybrid model which employs analytic network process (ANP) and modified TOPSIS (Technique for Order Performance by Similarity to Idea Solution) together, is proposed for the personnel selection problem. The ANP is used to analyze the structure of the personnel selection problem and to determine weights of the criteria, and modified TOPSIS method is used to obtain final ranking. To illustrate how the approach is used for the personnel selection problem, an application of a real case in a company is conducted. The application has demonstrated the effectiveness and feasibility of the proposed model. Company management found the application and results satisfactory and implementable in their personnel selection process.

A hybrid MCDM model for strategic vendor selection

Proposed in this study is a hybrid model for supporting the vendor selection process in new task situations. First, the vendor evaluation problem is formulated by the combined use of the multi-criteria decision-making (MCDM) approach and a proposed five-step hybrid process, which incorporates the technique of an analytic network process (ANP). Then the modified TOPSIS (technique for order performance by similarity to idea solution) is adopted to rank competing products in terms of their overall performances. The newly developed ANP will eventually yield the relative weights of the multiple evaluation criteria, which are obtained from the nominal group technique (NGT) with interdependence. An example is solved to illustrate the effectiveness and feasibility of the suggested model. The empirical study has demonstrated how the approach can be used for the strategic vendor selection problem.

COTS evaluation using modified TOPSIS and ANP

This paper models the COTS evaluation problem as an MCDM problem and proposes a five-phase COTS selection model, combining the technique of ANP (analytic network process) and modified TOPSIS (technique for order performance by similarity to idea solution). This article discusses using the ANP to determine the relative weights of multiple evaluation criteria. The modified TOPSIS approach is used to rank competing products in terms of their overall performance. To illustrate how the approach is used for the COTS evaluation problem, an empirical study of a real case is conducted. The case study demonstrates the effectiveness and feasibility of the proposed evaluation procedure.