A multi-attribute decision-making strategy for project management using the modified TOPSIS of multi-valued multi-polar neutrosophic hypersoft sets

Lipstick is a cosmetic usually worn by women to improve appearance with apply to the lips. The interest on lipstick among student at indonesia based on the various brands lipstick of national and international land of selling in indonesia. Based on this condition , it takes a method that can evaluate most favorite brand lipstick according to college student . The method applied to choose most favorite brand lipstick are Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Both this method can do the decision to establish an alternative best of a number of alternatives based on a number of certain criteria in overcoming Multi Attribute Decision Making (MADM), The concept of SAW is looking for a sum of the weighted performance rating for each alternative in all criteria. While TOPSIS using the principle that alternative chosen should have the shortest distance of a solution ideal positive and farthest of a solution ideal negative. There are 10 alternative brand lipstick and 10 criteria, the criterias are the price, color, form, packaging, resilience, pigmentation, texture, scent, the availability of code expired lipstick. The result of the research indicated that to the SAW method most favorite brand lipstick is of NYX and to the TOPSIS method most favorite brand lipstick is Wardah. The research also produce an application programming GUI Matlab that can help users in process data uses the method saw and topsis for an election most favorite brand lipstick. Keywords : GUI, Lipstick, MADM, SAW, TOPSIS

Multi-Attribute Decision Making (MADM) is a method of decision-making to establish the best alternative from a number of alternatives based on certain criteria. Some of the methods that can be used to solve MADM problems are Simple Additive Weighting (SAW) Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). SAW works by finding the sum of the weighted performance rating for each alternative in all criteria. While TOPSIS uses the principle that the alternative selected must have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution. Both of these methods were applied in making the selection of the best tourist attractions in Central Java. There are 15 tourist attractions and 7 criteria: location, infrastructure, beauty, atmosphere, tourist interest, promotion, and cost. This primary research employed a questionnaire that passed the questionnaire testing, namely its validity and reliability test. The result of this study shows that the best type of tourism according to the government is temple tour. While water sports tourism is favored by tourism observers. As for college students, the preferred tourist destination is religious tourism. This study also produced a GUI Matlab programming application that can help users in performing data processing using SAW and TOPSIS to select the best attraction in Central Java. Keywords : MADM, SAW, TOPSIS, GUI, tourism

In Heterogeneous Wireless Networks (HWNs), the mobile terminals are equipped with multiple access network interfaces (GSM, UMTS, LTE, WiFi, Bluetooth, etc.), to provide the possibility for mobile end-users to rank the networks and dynamically select the best one at anytime and anywhere, which is well known as Always Best Connected (ABC). In such environment, the major issue is network interface selection, which is a decision making problem with multiple alternatives (networks) and attributes (network characteristics, application requirements, terminal capacities, and user needs). In this context, many approaches have been proposed. Multi Attribute Decision Making (MADM) algorithms present a promising solution for multi-criteria decision making problems. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of MADM algorithms, which is widely adopted. TOPSIS ranks the available networks based on their scores, with the highest being the best. TOPSIS suffers from couple limitations. First is the ranking abnormality, e.g. if a low ranking network is disconnected then the order of higher ranking networks changes, which results in the selection of a less desirable network. Second is the selection strategy, where TOPSIS simply selects the network with highest score regardless of whether or not it satisfies the user and/or application needs. In this paper, we propose a new strategy based on utility function to remedy these shortcomings. The effectiveness of our strategy is evaluated through simulations. Obtained results show clearly that our strategy eliminates the rank reversal (ranking abnormality) phenomenon, and enhances the ranking quality by considering application and/or user needs.

Circular intuitionistic fuzzy (C-IF) sets are an up-and-coming tool for enforcing indistinct and imprecise information in variable and convoluted decision-making situations. C-IF sets, as opposed to typical intuitionistic fuzzy sets, are better suited for identifying the evaluation data with uncertainty in intricate realistic decision situations. The architecture of the technique for order preference by similarity to ideal solutions (TOPSIS) provides powerful evaluation tools to aid decision-making in intuitionistic fuzzy conditions. To address appraisal issues associated with decision analysis involving extremely convoluted information, this paper propounds a novel C-IF TOPSIS approach in the context of C-IF uncertainty. This research makes three significant contributions. First, based on the three- and four-term operating rules, this research introduces C-IF Minkowski distance measures, which are new generalized representations of distance metrics applicable to C-IF values and C-IF sets. Such general C-IF distance metrics can alleviate the constraints of established C-IF distance measures, provide usage resiliency through parameter settings, and broaden the applicability of metric analysis. Second, unlike existing C-IF TOPSIS methods, this research fully utilizes C-IF information characteristics and extends the core structure of the classic TOPSIS to C-IF contexts. With the newly developed C-IF Minkowski metrics, this study faithfully demonstrates the trade-off evaluation and compromise decision rules in the TOPSIS framework. Third, this research builds on the core strengths of the pioneered C-IF Minkowski distance measures to create innovative C-IF TOPSIS techniques utilizing four different combinations, including displaced and fixed anchoring frameworks, as well as three- and four-term representations. Such a refined C-IF TOPSIS methodology can assist decision-makers in proactively addressing increasingly sophisticated decision-making problems in practical settings. Finally, this research employs two innovative prioritization algorithms to address a site selection issue of large-scale epidemic hospitals to illustrate the superior capabilities of the C-IF TOPSIS methodology over some current related approaches.

To analyse the challenges that nurse managers meet in project management. Project management done by nurse managers has a significant role in the success of projects conducted in work units. The data were collected by open interviews (n = 14). The participants were nurse managers, nurses and public health nurses. Data analysis was carried out using qualitative content analysis. The three main challenges nurse managers faced in project management in health-care work units were: (1) apathetic organization and management, (2) paralysed work community and (3) cooperation between individuals being discouraged. Nurse managers' challenges in project management can be viewed from the perspective of the following paradoxes: (1) keeping up projects-ensuring patient care, (2) enthusiastic management-effective management of daily work and (3) supporting the work of a multiprofessional team-leadership of individual employees. It is important for nurse managers to learn to relate these paradoxes to one another in a positive way. Further research is needed, focusing on nurse managers' ability to promote workplace spirituality, nurse managers' emotional intelligence and their enthusiasm in small projects.

Technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi attribute decision making (MADM) method and it has been widely used in materials selection. However, the main drawback of the traditional TOPSIS is that it has a rank reversal phenomenon. To overcome this drawback, we propose an improved TOPSIS without rank reversal based on linear max-min normalization with absolute maximum and minimum values by modifying normalization formula and ideal solutions. Moreover, to study the impacts of changing attribute weights on relative closeness values of alternatives, we propose a sensitivity analysis method to attribute weights on the relative closeness values of the alternatives. We applied the proposed method to select best absorbent layer material for thin film solar cells (TFSCs). As a result, copper indium gallium diselinide was selected as the best one and the next cadmium telluride from among five materials. When the alternative is added to or removed from the set of original alternatives, the elements of the normalized decision-matrix, PIS, NIS and the relative closeness values don’t change at all, they are always coincide with the corresponding elements of the original ones. The relative closeness values are absolute values irrelevant to the composition of the alternatives in the improved TOPSIS, while the relative closeness values are relative values relevant to the composition of the alternatives in the traditional TOPSIS. Therefore, the proposed TOPSIS overcomes the rank reversal phenomenon, perfectly. It could be actively applied to practical problems for materials selection.

The study examined the challenges of project management in public property development projects in Niger Delta Region of Nigeria. The study revealed twenty three challenges of project management that is often time been faced by property developers during the development of public project. The public sector is known for multiple layers of reporting line (Stakeholder structure) and this poses huge challenges and as such the study looked at these issues and how they can affect the development of public projects. The study adopted a pragmatic research philosophy with qualitative and quantitative research approach. Qualitative and quantitative data were collected using twelve (12Nr) semi-structured interview, and one hundred and thirty (130Nr) questionnaires. The data was analysed using descriptive analysis techniques with relative important index (RII) and transcribing of data. Further, the result of the study shows that there are twenty three challenges of project management, but that project delivery time, quality management and procurement management is the most critical challenges. The study recommends that a project management office should be established and occupied by a professional (estate surveyor and valuer) especially who is trained in the project management body of knowledge. It is believed that this paper in no small measure will assist government’s officials, project managers, builders, clients and other stakeholders in the public sector, in checkmating the challenges of project management and improving public project delivery.

There is a natural tendency for stakeholder groups to try to influence the implementation of construction projects in line with their individual concerns and needs. This presents a challenge for construction project managers in analysing and managing these various concerns and needs in a stakeholder management process falling within the limits of the project. The aim of the research presented here was to show the factors affecting the stakeholder management process positively or negatively from the perspective of project implementation. A comparative study of two railway projects in Sweden was undertaken to analyse these factors. The study showed that the outcome of the stakeholder management process depended mainly upon how well the project managers presented the benefits and negative consequences brought on by the construction project. Techniques and tools exist for this purpose, but must be appropriate, and these are discussed in the context of the two projects. The challenge for project managers is to implement the project in such a way that the effects of negative impacts are minimized and, if possible, the benefits for all stakeholders are maximized. Project managers must communicate and interact with stakeholders so that the perceived benefits and negative impacts are realistically defined.

Tembalang is an area that has many culinary business. One of them is cafe bussiness. This condition causes high competition in attracting consumers to gain profit. According to this situation, we need a method to asses the most favourite cafe based on consumer taste to create cafe as they expected. The methods used in choosing the most favourite cafe are Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Both of method are the methods used to solve the Multi-Attribute Decision Making (MADM) problem. AHP is used as a method of weighting each criteria by forming pairwise comparison matrix, normalizing pairwise comparison matrix, weighting and testing the consistency of the weight that was gained. Whereas TOPSIS is used to rank the most favorite cafe by calculating the weighted-normalized decision matrix MADM, determining the positive and negative ideal solution, calculating the distance between each alternative with positive and negative ideal solution and calculating the value of preference for each alternatives. There are eight cafes and fourteen criterias. The criterias are the taste of foods and drinks, price, site accessibility, wifi, the neatness of waiters, the hospitality of waiters, waiters’s knowledge about menu, the accuracy of the preparation of the foods and drinks, transaction convenience, varian of menu, the safety and cleanliness of area, handling against misstatement, layout and decoration, and serving. The result of this research is: the most preferred cafe has 0.84322 of preference value. Preference value which calculated manually has similar result with Graphical User Interface (GUI) Matlab. Keywords : AHP, TOPSIS, cafe, favorite, preference

An extended TOPSIS model based on the Possibility theory under fuzzy environment

Multiattribute decision making (MADM) uses a normalization procedure to transform performance ratings with different data measurement units in a decision matrix into a compatible unit. MADM methods generally use one particular normalization procedure without justifying its suitability. The technique for order preference by similarity to ideal solution (TOPSIS) is one of the most popular and widely applied MADM methods. This study compares four commonly known normalization procedures in terms of their ranking consistency and weight sensitivity when used with TOPSIS to solve the general MADM problem with various decision settings. The comparison study is validated using two performance measures: ranking consistency and weight sensitivity. A large number of MADM problems with varying attributes and alternatives are generated using a new simulation technique. The study results justify the use of the vector normalization procedure for TOPSIS and provide suggestive insights for using other normalization procedures in certain decision settings.

Selection of the appropriate automated guided vehicle (AGV) for a manufacturing company is a very important but at the same time a complex problem because of the availability of wide-ranging alternatives and similarities among AGVs. Although, the available studies in the literature developed various fuzzy models, they do not propose any approaches to measure the benefits generated by incorporating fuzziness in their selection models. This paper aims to fill this gap by trying to quantify the level of benefit provided by employing the fuzzy numbers in the multi attribute decision making (MADM) models. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used as the MADM approach to rank the AGV in this paper. In the paper, by increasing the fuzziness level steadily in the fuzzy numbers, the obtained AGV rankings are compared with the ranking obtained with the crisp values. The statistical significance of the differences between the ranks is calculated using Spearman’s rank-correlation coefficient. It can be observed from the results that as the vagueness and imprecision increases, fuzzy numbers instead of crisp numbers should be used. On the other hand, in situations where there is a low level of fuzziness or the average value of the fuzzy number can be guessed, using crisp numbers will be more than adequate.KeywordsAGV selectionMulti Attribute Decision Making (MADM) Fuzzy numbersTechnique for Order Preference by Similarity to Ideal Solution (TOPSIS)

Due to a deployment of different networks technologies such as 3G (UMTS, IEEE 802.11), 4G (LTE, IEEE 802.16) and 5G, the users have the opportunity to be connected to Internet at any time and any where. This ability to be quickly and easily connected is ensured by using the intelligent mobile terminal multi-modes such as mobile phones, smart-phones, IPAD, etc. These equipments mobiles have enabled users also to handle simultaneously various applications by using different access networks. The most issue in this heterogeneous wireless network is enabling for users to continuously choose the most appropriate access network during their communication. To deal with this task, we propose a new approach for network selection based on two multi attribute decision making (MADM) methods namely multiple analytic network process (M-ANP) and technique for order preference by similarity to ideal solution (TOPSIS) method. The M-ANP is used to weigh each criterion and TOPSIS is applied to rank the alternatives. The simulation results illustrate the effectiveness of our optimized approach in terms of reducing of the reversal phenomenon and the ping-pong phenomenon.

New product development demands the analysis of each of the component from various engineering concepts.If a machine is expected to have a mechanical power transmission system, obviously number of options can be thought of.The power transmission system involves many hardware and many options are available.These mechanical drives are expected to be light,energy efficient and maintenance free. In the present work,a data matrix comprising of 10 attributes and 10 alternatives is presented .It is then operated for optimum selection in form of ramking using one of the welknown Multi Attribute Decision Making( MADM) method called Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).The results are given as ranking for the purpose of selectionwhich sets initiative for preliminary design.However the approach presented is also useful for existing designs which needs to be changed to enhance performance.

Background: Urban flooding and waterlogging in Bantul Regency stem from inadequate drainage systems, exacerbated by rapid urbanization, land use changes, poor infrastructure planning, and intensified rainfall due to climate change. Therefore, an integrated risk management approach compassing both structural and non-structural solutions—is crucial for improving urban drainage resilience. Conversely, the comprehensive evaluation of drainage system performance continues to pose considerable challenges. Assessments that concentrate solely on hydraulic or technical parameters while neglecting environmental, social, and economic factors—often result in suboptimal or misdirected decisions. As such, adopting a more integrative approach through multi-criteria decision-making methods, such as Multi-Attribute Decision Making (MADM), emerges as a pertinent alternative.Aims and Methods: The methods employed for MADM analysis in this study include the Simple Additive Weighting (SAW), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these approaches is designed to accommodate different data characteristics, levels of analytical complexity required, degrees of uncertainty involved, computational load, and the decision maker’s experience or expertise in applying the respective method.Results: The analysis results indicate that, based on the SAW method, location A11 obtained the highest score (0.8637), signifying the poorest drainage system performance and thus requiring top-priority intervention, whereas location A77 achieved the lowest score (0.3132), indicating a well-functioning drainage condition. Using TOPSIS, location A9 ranked first with a preference value (Vi) of 0.7498, reflecting significant proximity to the ideal solution, while A6 recorded the lowest score (0.2152). Meanwhile, the VIKOR method identified location A99 as the top-ranked alternative with a VIKOR index of 16.5321, while A1 emerged as the lowest-ranked alternative with a VIKOR index of 0.0188.