Essay Topics For the Year 2020

<h1>Essay Topics For the Year 2020</h1><p>If you are anticipating taking your composition to another level, at that point you should investigate the article themes for the year 2020. Not exclusively will this give you a few thoughts, however it will likewise give you a few insights on what will be the best articles that you can write.</p><p></p><p>This is the best season to compose papers on the grounds that these exposition points were chosen by an advisory group. This implies not exclusively will you read about these points, however you will likewise be going over a wide range of subjects so as to locate the correct theme for your individual needs.</p><p></p><p>The article subjects for the year 2020 incorporate history, current science, theory, brain science, topography, and writing. These are only a couple of the points that are introduced to understudies just as educators who need to compose articles that will intr igue their students.</p><p></p><p>Many understudies are keen on finding out about what the history exposition subjects are. Numerous educators would tell their understudies that on the off chance that they need to find out about the chronicled periods, they should explore every period first.</p><p></p><p>For model, in the event that they were attempting to show a history exercise, they would need to know the years that were secured by the various times and occasions. By finding out about what occurred during those occasions, they will have a superior thought of how the world was during that time.</p><p></p><p>The same goes for the recent developments that are going on the planet today. Understudies should realize what issues are going on with the goal that they will have the option to examine the present circumstances that influence individuals' lives.</p><p></p><p>The journalists who wil l be taking a shot at these themes will be in a situation to clarify how current science is utilized in various manners. By being able to clarify how science functions, the scholars will have the option to clarify the various parts of logical realities that will influence individuals' lives.</p><p></p><p>Teachers ought to likewise have the option to assist understudies with deciding how an individual's general character and contemplations about things depend on specific conditions. Subsequently, the understudy will have the option to think of the right answers that will be valuable in these cases.</p>

The Leaked Secrets to Essay Topics on the Power and the Glory Discovered

<h1>Essay Writing - How to Start Writing Your New School Essay</h1><p>There are a ton of contemplations that go into composing a proposition, and in this article we'll talk about a portion of the components to consider before really composing the paper. Composing a postulation is a significant endeavor, thus numerous understudies think that its troublesome from the outset, yet with a little practice they figure out how to compose their proposal with certainty. On the off chance that you are experiencing difficulty composing your proposition, here are a few hints to assist you with jumping on the privilege track.</p><p></p><p>The first thing you'll have to do is make a working title for your theory. This should be possible regarding a book or reading material blueprint, for instance. On the off chance that this isn't the situation, at that point you should make a work in progress of your proposition title. Additionally, you should attempt to p ick a reasonable title for your theory utilizing a term like homeopathy, which signifies 'dissolving something', in English. Homeopathy can possibly bring a novel point into the investigation of science and pharmacology.</p><p></p><p>While you're taking a shot at your proposition you ought to likewise be making foundation materials and insights concerning your examination. This will permit you to develop a structure that the peruser can follow when they inevitably begin perusing your proposition. At the point when you start taking a shot at your theory, you should likewise set up a layout, a figure of substance, and start writing.</p><p></p><p>You'll need to incorporate your significant research questions and significant research addresses that you would like to reply in your proposition. More often than not when you begin taking a shot at your proposal you ought to ask yourself a progression of inquiries about what you hope to pick up from your research.</p><p></p><p>Your last advance recorded as a hard copy your postulation ought to be to guarantee that it is finished and effectively designed. Check to ensure that you've finished all the areas required by your guide. Truth be told, guarantee that you have completely arranged your proposition by taking an assessment of your postulation. At the point when you do your postulation in your last draft, you will know whether there are any blunders in your theory. There is one more advance that you should take before you begin composing your theory - you should give your classes the task that you might want them to peruse on their next class task. The explanation behind this is numerous understudies can be quick to peruse your proposition all alone - along these lines, give them the task that you trust they will peruse. This is a significant part of composing a proposal, since it will guarantee that you will look extraordinary in the event that they give you an evaluation on your thesis.</p><p></p><p>Thesis composing is a significant piece of your instruction and requires both aptitude and imagination. In any case, on the off chance that you realize where to begin and what to do, at that point you will see a distinction in your grades.</p>

Essay Samples on Apps - How to Write Better Essays

Essay Samples on Apps - How to Write Better EssaysThere are many free essay samples on apps out there. The first question that is most asked when one hears of them is why would someone write an essay on apps if they have the money to spend? In short, it is because some people cannot afford to spend the money on the applications, and so, they cannot write the essays.Free programs are available, and many are very good. However, like with everything, you get what you pay for. If a person is willing to spend money on the application, they will be able to write the essay that they want.What are the free programs? Well, there are some that cost nothing, and some that do cost a small amount. To determine which one is right for you, try doing a simple search on the internet. You will find some free programs, but most of them cost a small amount of money.There are hundreds of websites that offer essay samples on apps. Before you begin using any of these sites, however, you should make sure th at you know what type of application that they are offering.A free program will not contain all of the necessary information to write an essay. Many of the sites that offer free programs do not have enough content on them to help you. They will only get you started.As you continue using the site, you will see that it will increase in terms of essays. Now, there are certain things that you should look for in a free program. If you are able to find one that has everything that you need, that would be the best program to use.The sites that have free programs are also able to help you learn how to write better. These programs will tell you the things that you need to do to improve your essays. By using this, you will be able to write the essays that you want to write.Do not worry about using essay samples on apps, as it is possible to do. Some of these programs can actually get you started on the right track. Use the right one and you will be writing more articles that will get you wher e you want to be.

Auto Industry Facts

Auto Industry FactsWhen you are researching the market for your automobile research paper topics, you will be surprised at how many unique and important questions arise out of every situation. You must be able to understand what is happening within your company when you are conducting this type of research. When this is the case, it is easy to miss many of the most significant and crucial points to the automobile industry.The fact of the matter is that all of the major automakers have suffered substantial losses for quite some time. They have lost customers and have many problems with maintaining and repairing their vehicles. How can any automaker possibly lose a business when they are one of the most profitable businesses in the world?In the auto industry, the present is a difficult time to be having to business owners. It is clear that many consumers are seeking alternative sources for buying automobiles. The cost of fuel is at record highs and that makes owning an automobile less practical for many consumers.Going forward, those consumers who do not purchase from an independent dealer will often look to the used car market. This appears to be an alternative to purchasing a brand new automobile. The question that consumers will need to ask themselves 'Does owning a second hand automobile make sense for me?'Many individuals who shop in the used car market often times do so from a dealership that is affiliated with numerous dealer. These individuals are making a calculated choice to purchase their used vehicles from a third party dealer. Is this wise?The answer to this question is absolutely vital when it comes to answering any number of good research paper topics. If you want to be successful in the automobile industry, you must be able to answer these questions in an effective and efficient manner. Your vehicle purchase should not be a gamble.Keep in mind that the auto industry is in a very volatile and challenging environment right now. The fact of the matte r is that the number of dealers is decreasing each year. Many of them are competing in this environment by aggressively advertising their products to a wide range of customers.While there is no doubt that consumers do need to be offered alternative sources for purchasing their investment vehicle, this does not mean that you have to shy away from your primary dealership. You need to remain confident in your ability to provide your customers with a great product and service. You will not find one that has done a great job at creating a satisfied customer.

Interval Valued Intuitionistic Fuzzy Soft Multi Set Theoretic Approach to Decision Making Problems - Free Essay Example

Interval Valued Intuitionistic Fuzzy Soft Multi Set Theoretic Approach to Decision Making Problems Abstractà ¢Ã¢â€š ¬Ã¢â‚¬ In recent years the application of soft set in decision making problems has been developed rapidly since it can be applied easily to several areas like computer science, information technology, medical science, economics, environments, engineering, among other areas. In this paper, we give the application of interval-valued intuitionistic fuzzy soft multisets in real life decision making problems and proposed an algorithm to solve multi weighted interval valued intuitionistic fuzzy soft multiset based decision making problems by using weighted choice values. The feasibility of our proposed algorithm in practical applications is illustrated by a numerical example. Keywordsà ¢Ã¢â€š ¬Ã¢â‚¬ soft set; level soft set; weighted function; interval valued intuitionistic fuzzy soft sets; interval valued intuitionistic fuzzy soft multi set; decision ma king. . I. Introduction The concept of soft set theory was first initiated by Molodstov [18] in 1999 as an important mathematical tool for dealing with vagueness, uncertainties and not clearly defined objects. Some new algebraic operations and results on soft set theory defined in [[2], [17]]. Adding soft sets [12] with fuzzy sets [15] and intuitionistic fuzzy sets [5], Maji et al. [13-16] defined fuzzy soft sets and intuitionistic fuzzy soft sets and studied their basic properties. As a generalization of soft set, Alkhazaleh and others [[1], [4], [7], [8], [26]] defined the notion of a soft multi set and its basic algebraic structures and general topological structures were studied. In 2007, Roy and Maji [21] presented a novel method to cope with fuzzy soft sets based decision making problems. Kong et al. [8] mentioned that the Roy-Maji algorithm [13] was wrong and they introduced a revised algorithm. Feng et al. [[9], [10]] studied the validity of the Roy-Maji algorithm [21] and mentioned that the Ro y-Maji Algorithm [13] has some limitations. Also, they proposed an adjustable approach to fuzzy soft sets based decision making problems by using thresholds and choice values and gave the application of level soft sets in decision making based on interval-valued fuzzy soft sets. Jiang et al. [11] studied interval-valued intuitionistic fuzzy soft sets and their properties. There after Zhang et al. [24] presented a novel approach to interval-valued intuitionistic fuzzy soft set based decision making. In 2012, Alkhazaleh and Salleh [3] initiated the notion of fuzzy soft multi set theory as a generalization of soft multi set theory and presented its application in decision making using Roy-Maji Algorithm [21]. As a generalization of fuzzy set theory [23], intuitionistic fuzzy set theory [5] and interval-valued intuitionistic fuzzy set theory [6] makes descriptions of the objective more realistic, practical and accurate. Mukherjee and Das [19] introduced the concepts of intuitionistic fuzzy soft multi sets and studied intuitionistic fuzzy soft multi topological spaces in detail. Mukherjee et al. [20] also introduced the concepts of interval valued intuitionistic fuzzy soft multi sets and studied their relation in details. In this study, we have proposed an algorithm to solve multi weighted interval valued intuitionistic fuzzy soft multiset based decision making problems by using weighted choice values. The feasibility of our proposed algorithm in practical applications is illustrated with a numerical example. II. Preliminary Notes In this present section, we briefly recall some basic notions of soft set, interval valued intuitionistic fuzzy set, interval valued intuitionistic fuzzy soft multi set and level soft set. Suppose that, U be an initial universe and E be a set of parameters. Also, let P(U) denotes the power set of the universe U and Aƒ E. Definition 2.1 ([20]). A pair (F, A) is said to be a soft set over the universe U, where F is a mapping given by F: A ® P(U). Definition 2.2 ([6]). An interval valued intuitionistic fuzzy set (in short IVIF-set) A over a universe set U is defined as the object of the form where MY(x): U ®INT([0,1]) and NY(x): U ®INT([0,1]) are functions such that the condition: à ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¢xÆ’Å ½U, 0 £ sup MY(x)+sup NY(x) £1 is satisfied (where INT[0,1] is the set of all closed intervals of [0,1]). Definition 2.3 ([24]). Suppose that be a set of universes, such that and let for each , be a sets of decision parameters. Also, let where is the set of all interval valued intuitionistic fuzzy subsets of , and . A pair is said to be an interval valued intuitionistic fuzzy soft multiset (in short IVIF-soft multiset) over the universe U, where F is a function given by F: A ® U, such that For illustration, we consider the following house, car and hotel example. Example 1. Let us consider three universes U1= {h1, h2, h3}, U2= {c1, c2, c3} and U3= {v1, v2, v3} are the sets of houses, cars and hotels respectively and let be the sets of respective decision parameters related to the above three universes. Let , and , such that Assume that, Mr. X wants to buy a house, a car and rent a hotel with respect to the three sets of decision parameters as in above. Suppose the resultant IVIF-soft multiset be given in TABLE I. ivif-Soft Multiset (F, A) Ui a1 a2 a3 a4 a5 U1 h1 h2 h3 ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.4]) ([0.4,0.5], [0.3,0.4]) ([0.4,0.6], [0.1,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.1,0.3], [0.4,0.6]) ([0.5,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.7,0.8], [0.1,0.2]) ([0.6,0.7], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.5]) ([0.5,0.6], [0.3,0.4]) U2 c1 c2 c3 ([0.6,0.8], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.4,0.5], [0.3,0.4]) ([0.5,0.6], [0.1,0.2]) ([0.5,0.6], [0.2,0.4]) ([0.6,0.7], [0.1,0.2]) ([0.3,0.4], [0.3,0.4]) ([0.4,0.8], [0.1,0.2]) ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.3,0.7], [0.1,0.3]) ([0.4,0.5], [0.3,0.4]) ([0.6,0.7], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) U3 v1 v2 v3 ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) ([0.5,0.6], [0.2,0.3]) ([0.4,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.3,0.7], [0.1,0.3]) ([0.4,0.6], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.2,0.4], [0.3,0.5]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.3,0.4], [0.4,0.6]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) Definition 2.4 ([28]). Suppose that,  Ãƒâ€šÃ‚ ¶= (F, A) be an IVIF-soft set over U, where Aƒ E and E is the parameter set. Let  Ãƒâ€šÃ‚ ¬: A ® INT[0,1] ´INT[0,1] be an IVIF-set in A, which is called a threshold IVIF-set. The level soft set of  Ãƒâ€šÃ‚ ¶ with respect to  Ãƒâ€šÃ‚ ¬ is a crisp soft set L( Ãƒâ€šÃ‚ ¶; Ãƒâ€šÃ‚ ¬) = (F Ãƒâ€šÃ‚ ¬, A) defined by F Ãƒâ€šÃ‚ ¬(e) = {uÆ’Å ½U: [ Ãƒâ€šÃ‚ ­LF(e)(u), Ãƒâ€šÃ‚ ­UF(e)(u)]  ³ [ Ãƒâ€šÃ‚ ­L Ãƒâ€šÃ‚ ¬(e), Ãƒâ€šÃ‚ ­U Ãƒâ€šÃ‚ ¬(e)] and [ Ãƒâ€šÃ‚ ®LF(e)(u), Ãƒâ€šÃ‚ ®UF(e)(u)]  £ [ Ãƒâ€šÃ‚ ®L Ãƒâ€šÃ‚ ¬(e), Ãƒâ€šÃ‚ ®U Ãƒâ€šÃ‚ ¬(e)] }, à ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¢eÆ’Å ½A. According to the definition, four types of special level soft set as Mid-level soft set L( Ãƒâ€šÃ‚ ¶; mid), Top-Bottom-level soft set L( Ãƒâ€šÃ‚ ¶; topbottom), Top-Top-level soft set L( Ãƒâ€šÃ‚ ¶; toptop) and Bottom-bottom-level soft set L( Ãƒâ€šÃ‚ ¶; bottombottom) are defined in [11]. III. Multi Weighted ivif-Soft Multiset In this present section, we introduce the concept of multi weighted IVIF-soft multiset and examine its application for decision making problems. If we allow the parameters to have different multi weights, then the multi weighted version of the IVIF-soft multiset can be defined as follows. Definition 3.1. A multi weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶ is a triple where (F, A) is an IVIF-soft multiset over U and is a multi weight function, where I = [0,1], specifying the weight wk= Ãƒâ€šÃ‚ ·(ak) for each attribute akÆ’Å ½A and a triple is called a Ui-weighted IVIF-soft multiset part of  Ãƒâ€šÃ‚ ¶, where is a Ui IVIF-soft multiset part of (F, A) and is a weight function. Example 2. If we consider the IVIF-soft multiset be (F, A) as in TABLE I and suppose that Mr. X has imposed the following weights for the parameters in A: for the parameters Then we have a weighted  Ãƒâ€šÃ‚ · for an IVIF-soft multiset (F, A), where and the IVIF-soft multiset (F, A) is changed into a multi weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶ = with its tabular representation as in TABLE II. Multi Weighted ivif-Soft Multiset  Ãƒâ€šÃ‚ ¶ Ui a1, (0.7, 0.8,0.8) a2, (0.8, 0.7.0.6) a3, (0.7, 0.6,0.5) a4,(0.5, 0.3,0.4) a5,(0.7, 1,0.6) U1 h1 h2 h3 ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.4]) ([0.4,0.5], [0.3,0.4]) ([0.4,0.6], [0.1,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.1,0.3], [0.4,0.6]) ([0.5,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.7,0.8], [0.1,0.2]) ([0.6,0.7], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.5]) ([0.5,0.6], [0.3,0.4]) U2 c1 c2 c3 ([0.6,0.8], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.4,0.5], [0.3,0.4]) ([0.5,0.6], [0.1,0.2]) ([0.5,0.6], [0.2,0.4]) ([0.6,0.7], [0.1,0.2]) ([0.3,0.4], [0.3,0.4]) ([0.4,0.8], [0.1,0.2]) ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.3,0.7], [0.1,0.3]) ([0.4,0.5], [0.3,0.4]) ([0.6,0.7], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) U3 v1 v2 v3 ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) ([0.5,0.6], [0.2,0.3]) ([0.4,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.3,0.7], [0.1,0.3]) ([0.4,0.6], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.2,0.4], [0.3,0.5]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.3,0.4], [0.4,0.6]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) Weighted U1 à ¢Ã¢â€š ¬Ã¢â‚¬Å"ivif-Soft Multiset Part of  Ãƒâ€šÃ‚ ¶ U1 a1 0.7 a2 0.8 a3 0.7 a4 0.5 a5 0.7 h1 h2 h3 ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.4]) ([0.4,0.5], [0.3,0.4]) ([0.4,0.6], [0.1,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.1,0.3], [0.4,0.6]) ([0.5,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.7,0.8], [0.1,0.2]) ([0.6,0.7], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.5]) ([0.5,0.6], [0.3,0.4]) IV. Multi Weighted ivif-Soft Multiset Theoretic Approch to Decision Making Based on Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm A. Zhang et alà ¢Ã¢â€š ¬Ã¢â€ž ¢s algorithm based on weighted choice values Zhang et al. [28] used the following adjustable approch to weighted IVIF-soft set based decision-making by using weighted choice values. Algorithm 1(Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm). Input a weighted IVIF-soft set  Ãƒ ¢Ã¢â€š ¬Ã‹Å" = lt;F, A,  Ãƒâ€šÃ‚ ·gt; Input a threshold IVIF-set  Ãƒâ€šÃ‚ ¬: A ®INT[0,1] ´INT[0,1] for decision making. Compute the level soft set L( Ãƒ ¢Ã¢â€š ¬Ã‹Å"; Ãƒâ€šÃ‚ ¬) of  Ãƒ ¢Ã¢â€š ¬Ã‹Å" with respect to the threshold IVIF-set  Ãƒâ€šÃ‚ ¬. Present L( Ãƒ ¢Ã¢â€š ¬Ã‹Å"; Ãƒâ€šÃ‚ ¬) in tabular form and obtain the weighted choice value Si of uiÆ’Å ½U, à ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¢i. The final optimal decision is to select uk if Sk = maxi Si. If k has more than one value then any one of uk may be chosen. B. Application of IVIF-soft multisets in decision-making problems In this section, we propose an algorithm (Algorithm 2) for IVIF-soft multi sets based decision making problems, using Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm [7], as described above. In the following, we have to show our algorithm (Algorithm 2): Algorithm 2. Input a multi weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶ =(F, A,  Ãƒâ€šÃ‚ ·) Apply Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm to the first weighted IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶ to get the decision Sk1. Modify the weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶ by keeping all values in each row where Sk1 is maximum and replacing the values in the other rows by zero, to get  Ãƒâ€šÃ‚ ¶1. Apply Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm to the second weighted IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶1 to get the decision Sk2 Modify the multi weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶1 by keeping the first and second parts and apply the method in step (3) to the third part. Apply Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm to the third weighted IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶2 to get the decision Sk3. Continuing in this way we get the final optimal decision (Sk1, Sk2, Sk3à ¢Ã¢â€š ¬Ã‚ ¦Ãƒ ¢Ã¢â€š ¬Ã‚ ¦). Remark 1. In the step (7) of our algorithm (Algorithm 2), if there are too many optimal choices obtained, then decision maker may go back to the step (2) as in our algorithm (Algorithm 2) and replace the level soft set (decision criterion) that he/she once used to adjust the final optimal decision. C. Application in decision-making problems Let us consider the decision making problem involving the multi weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶ with its tabular representation given by TABLE II. If we deal with this problem by mid-level decision rule, we shall use the mid-threshold of weighted U1- IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶ and we the mid-level soft set of weighted U1 IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶ with weighted choice values with tabular representation is in TABLE IV. Mid-Level Soft Set of Weighted U1-ivif-Soft Multiset Part of  Ãƒâ€šÃ‚ ¶ with Weighted Choice Values U1 a1 0.7 a2 0.8 a3 0.7 a4 0.5 a5 0.7 Choice value Weighted choice value(sk) h1 h2 h3 0 0 1 0 0 1 0 1 0 1 1 0 0 1 1 1 3 3 s1=0.5 s2=1.9 s3=2.2 From TABLE IV, it is clear that the maximum weighted choice value is 2.2, scored by h3. Now we redefine the weighted interval valued intuitionistic fuzzy soft multi set  Ãƒâ€šÃ‚ ¶ by keeping all values in each row where h3 is maximum and replacing the values in the other rows by zero, to get  Ãƒâ€šÃ‚ ¶1. Multi Weighted ivif-Soft Multiset  Ãƒâ€šÃ‚ ¶1 Ui a1, (0.7, 0.8,0.8) a2, (0.8, 0.7.0.6) a3, (0.7, 0.6,0.5) a4,(0.5, 0.3,0.4) a5,(0.7, 1,0.6) U1 h1 h2 h3 ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.4]) ([0.4,0.5], [0.3,0.4]) ([0.4,0.6], [0.1,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.1,0.3], [0.4,0.6]) ([0.5,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.7,0.8], [0.1,0.2]) ([0.6,0.7], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.5]) ([0.5,0.6], [0.3,0.4]) U2 c1 c2 c3 ([0.6,0.8], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.4,0.5], [0.3,0.4]) ([0.5,0.6], [0.1,0.2]) ([0.5,0.6], [0.2,0.4]) 0 0 0 0 0 0 ([0.4,0.5], [0.3,0.4]) ([0.6,0.7], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) U3 v1 v2 v3 ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) ([0.5,0.6], [0.2,0.3]) ([0.4,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.3,0.7], [0.1,0.3]) 0 0 0 0 0 0 ([0.3,0.4], [0.4,0.6]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) Now we apply Zhangà ¢Ã¢â€š ¬Ã¢â€ž ¢s Algorithm to the second weighted IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶1 to take the decision from the availability set U2. The tabular representation of the second resultant weighted IVIF-soft multiset part of  Ãƒâ€šÃ‚ ¶1 will be as in TABLE VI. Mid-Level Soft Set of Weighted U2-ivif-Soft Multiset Part in  Ãƒâ€šÃ‚ ¶1 with Weighted Choice Values U2 a1, 0.8 a2, 0.7 a3, 0.6 a4, 0.3 a5, 1 Choice value Weighted choice value(sk) c1 c2 c3 1 0 1 0 1 0 0 0 0 0 0 0 0 1 1 1 2 2 s1=0.8 s2=1.7 s3=1.8 From TABLE VI, it is clear that the maximum weighted choice value is 1.8, scored by c3. Now we redefine the weighted IVIF-soft multiset  Ãƒâ€šÃ‚ ¶1 by keeping all values in each row where c3 is maximum and replacing the values in the other rows by zero, to get  Ãƒâ€šÃ‚ ¶2. Multi Weighted ivif-Soft Multiset  Ãƒâ€šÃ‚ ¶2 Ui a1, (0.7, 0.8,0.8) a2, (0.8, 0.7.0.6) a3, (0.7, 0.6,0.5) a4,(0.5, 0.3,0.4) a5,(0.7, 1,0.6) U1 h1 h2 h3 ([0.2,0.3], [0.4,0.7]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.4]) ([0.4,0.5], [0.3,0.4]) ([0.4,0.6], [0.1,0.3]) ([0.7,0.8], [0.1,0.2]) ([0.1,0.3], [0.4,0.6]) ([0.5,0.7], [0.2,0.3]) ([0.2,0.4], [0.3,0.5]) ([0.7,0.8], [0.1,0.2]) ([0.6,0.7], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.2,0.3], [0.4,0.7]) ([0.4,0.5], [0.3,0.5]) ([0.5,0.6], [0.3,0.4]) U2 c1 c2 c3 ([0.6,0.8], [0.1,0.2]) ([0.5,0.6], [0.3,0.4]) ([0.7,0.8], [0.1,0.2]) ([0.4,0.5], [0.3,0.4]) ([0.5,0.6], [0.1,0.2]) ([0.5,0.6], [0.2,0.4]) 0 0 0 0 0 0 ([0.4,0.5], [0.3,0.4]) ([0.6,0.7], [0.2,0.3]) ([0.7,0.8], [0.1,0.2]) U3 v1 v2 v3 ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) ([0.5,0.6], [0.2,0.3]) 0 0 0 0 0 0 0 0 0 ([0.3,0.4], [0.4,0.6]) ([0.5,0.6], [0.3,0.4]) ([0.5,0.8], [0.1,0.2]) Now we apply Algorithm 1 to the third weighted IVIF-soft multiset part in  Ãƒâ€šÃ‚ ¶2 to take the decision from the availability set . The tabular representation of the third resultant weighted IVIF-soft multiset part of  Ãƒâ€šÃ‚ ¶2 is as in TABLE VIII. Mid-Level Soft Set of Weighted U3-ivif-Soft Multiset Part in  Ãƒâ€šÃ‚ ¶2 with Weighted Choice Values U3 a1, 0.8 a2, 0.6 a3, 0.5 a4, 0.4 a5, 0.6 Choice value Weighted choice value(sk) v1 v2 v3 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 s1=0 s2=0.8 s3=0.6 From the TABLE VIII, we have to seen that the maximum weighted choice value is 0.8, by v2. Thus from above results, the final optimal decision for decision maker Mr. X is (h3, c3, v2). Remark 2. From the above illustration, we have seen that our algorithm (Algorithm 2) is too simple and less computation. We have to consider only weighted choice values of objects in thresholds of weighted IVIF-soft multiset part. Also, our algorithm (Algorithm 2) is an adjustable algorithm, because the level soft set (decision rule) used by decision makers, which are changeable. For example, if we take top-level decision criterion in step (2) of our algorithm (Algorithm 2), then we have the weighted choice value of each object in the top-level soft set of weighted IVIF-soft multiset parts in the multi weighted IVIF-soft multiset, if we take another decision rule such as the mid-level decision criterion, then we have weighted choice values from the mid-level soft set of weighted IVIF-soft multiset parts in the multi weighted IVIF-soft multiset. Generally, the weighted choice values of a same object in the mid-level decision rule and in the mid-level decision rule are need not coincide. V. Conclusion In this research work, the notion of multi weighted IVIF-soft multiset is to be defined and also, we propose an adjustable approach to multi weighted IVIF-soft multiset based decision making by using weighted choice values and illustrate this algorithm with a numerical example. In our algorithm, a multi weighted IVIF-soft multiset is converted into a crisp soft set for solving decision making problems after considering certain opinion weighting vectors and thresholds. This makes our algorithm simpler and easier for real life practical applications. The feasibility of our proposed algorithm in real life practical problems is illustrated with a numerical example.