Identification Of A Better Laptop With Conflicting .
I.J. Information Engineering and Electronic Business, 2015, 6, 28-36Published Online November 2015 in MECS (http://www.mecs-press.org/)DOI: 10.5815/ijieeb.2015.06.05Identification of a Better Laptop with ConflictingCriteria Using TOPSIST. Miranda LakshmiResearch Scholar, Research and Development Centre, Bharathiyar University, Coimbatore, India.Email: cudmiranda@gmail.comV. Prasanna VenkatesanAssociate Prof., Department of Banking Technology, Pondicherry University, Puducherry, India.Email: prasanna v@yahoo.comA. MartinAssociate Professor, Department of MCA, Sri Manakula Vinayagar Engg. College, Puducherry, India.Email: jayamartin@yahoo.com, cudmartin@gmail.comAbstract—Multi Criteria Decision Making (MCDM)methods are useful for evaluating several complex factorsof multiple selection problems. The Multi-Objectiveproblems are an extension of Single-Objective problems.The goal of MCDM is to help the decision maker tomake a choice among a finite number of alternatives or tosort or rank a finite set of alternatives in terms of multiplecriteria. Among the MCDM methods, the most widelyapplied method is TOPSIS. It is applied for differentkinds of MCDM problems. In laptop selection process, itis difficult to select better laptop because relatively alllaptops are seems to be same. By applying the TOPSISmethod to the alternatives it is simple to differentiate thelaptops from one another. The better laptop has beenselected using TOPSIS based on conflicting criteria suchas warranty, size, battery life, specification and others.This methodology also has been evaluated by MCDMevaluation metrics such as Time and Space Complexity,Sensitivity Analysis, ranking reversal and relativecloseness coefficient.Index Terms—Multi Criteria Decision Making (MCDM),TOPSIS, evaluation metrics, laptop selection, rankingefficiencyI. INTRODUCTIONDecision-making can be regarded as the cognitiveprocess resulting in the selection of a belief or a course ofaction among several alternative possibilities. It is thestudy of identifying and choosing alternatives based onthe values and preferences of the decision maker. Multicriteria decision making (MCDM) is the process offinding the best alternative from all of the feasiblealternatives where all the alternatives can be evaluatedaccording to a number of criteria or attribute (Tan &Chen, 2010). It refers to screening, prioritizing, ranking,or selecting a set of alternatives under usuallyindependent, incommensurate or conflicting attributesCopyright 2015 MECS(Hwang & Yoon, 1981) [1].The goal of MCDM is to help the decision maker (DM)to make a choice among a finite number of alternatives orto sort or rank a finite set of alternatives in terms ofmultiple criteria. The widely used MCDM methods areAnalytic Hierarchy Process (AHP), Grey RelationalAnalysis (GRA), ELECTRE (Elimination EtChoixTraduisant la REalite, Technique for the Order ofPrioritization by Similarity to Ideal Solution (TOPSIS),VIKOR, etc. Among the different MCDM techniques,the most widely applied method is TOPSIS [2]. It is oneof the widely applied MCDM techniques to solve multicriteria decision making problem (Hwang and Yoon,1981). It is based on the principle that the chosenalternative should have the longest distance from thenegative-ideal solution, i.e. the solution that maximizesthe cost criteria and minimizes the benefits criteria, andthe shortest distance from the positive-ideal solution, i.e.,the solution that maximizes the benefit criteria andminimizes the cost criteria. It is applied to find the betteralternative when more number of conflicting criteria isavailable.In this research, TOPSIS has been applied to find thebetter laptop. Today different kinds of laptops areavailable. Identification of difference between this laptopis very difficult. In this research Cost, Warranty, Size,Battery life, Specification (RAM, Processor, graphicscard, speed), genuine operating system, weight of thelaptop, Wi-Fi and Touch pad are considered as criteria tofind the better laptop. It is difficult to select better laptopbecause relatively all laptops are seems to be similar. Byapplying TOPSIS method to the alternatives based on thecriteria the laptops can be differentiated. In this research,MCDM evaluation metrics are applied to evaluate thelaptop selection problem.The rest of the paper is organized as section 2describes about literature review on different applicationdeveloped using TOPSIS. Section 3 describes theresearch proposal; section 4 describes the researchmethodology, section 5 describes about experimentationI.J. Information Engineering and Electronic Business, 2015, 6, 28-36
Identification of a Better Laptop with Conflicting Criteria Using TOPSISdetails, section 6 discusses the results and section 7concludes the research.29evaluated using MCDM parameters. In this research,better laptop is identified using TOPSIS. This proposedapplication is evaluated using MCDM parameters.II. LITERATURE REVIEWSelection the right vendor for a long term relationshipis a relevant procurement issue that demands judiciousattention. The finding of a most suitable supplier is oneof the most important issues to establish an effectivesupply chain system [3]. Indeed, supplier selection andevaluation represents one of the significant roles ofpurchasing and supply management function. Tracey andTan (2001) note that one of the key elements essential tosupply chain success is effective purchasing function [4].Lee et al. (2001) and Kumara et al. (2003) emphasize thatselection of the best supplier is an essential strategic issueimperative for supply chain effectiveness and efficiency.Kumara et al. (2003) contend that strategic partnershipwith the right supplier must be integrated within thesupply chain to contain costs, improve quality andflexibility to meet end-customers' value and reduce leadtime at different stages of the supply chain (Chris I., BellHanyes, 2010) [5].A study by Moynihan et al. (2006), states that about 60%of the manufacturer's sales dollars are paid to the supplierfor purchased materials [6]. Most of those costs occur inthe first stage of supply chain i.e., supplier selection. Asmentioned by Venkata Rao (2007), supplier performanceis a key issue which affects the success or failure oforganizations. Any supply chain is initiated with theselection of right suppliers for the raw materials(Parthiban et al. 2010).Supplier selection decisions are complicated by thefact that various criteria must be considered in thedecision making process. The analysis of criteria forselection and measuring the performance of suppliers hasbeen the focus of many academicians and purchasingpractitioners since 1960s [7]. (Weber, Current, Benton,1991) Based on Dickson's (1966) empirical study, 23criteria were identified which purchasing managersgenerally consider when selecting a supplier. Dempsey(1978) identified quality, delivery capability, andtechnical capability as imperative in supplier selection.Ellram (1990) emphasized the need not only to basesupplier selection decision on the traditional price andquality criteria but also on longer term and qualitativeattributes such as strategic match and evaluation of futuremanufacturing capabilities [8].III. RESEARCH PROPOSALFrom the literature it has been found that very limitedmetric such as time and space complexity has beenapplied for TOPSIS. These metrics are applied toevaluate different kinds of TOPSIS applications. In thisresearch, in addition to existing metric sensitivityanalysis and ranking reversal are defined to evaluate theTOPSIS applications. In this research better laptop isidentified using TOPSIS. This proposed application isCopyright 2015 MECSIV. DESIGN OF RESEARCH METHODOLOGYMCDA is a sub-discipline of operations research thatexplicitly considers multiple criteria in decision-makingenvironments [9]. In our daily lives or in professionalsettings, there are typically multiple conflicting criteriathat need to be evaluated in making decisions. Cost orprice is usually one of the main criteria [10]. Somemeasure of quality is typically another criterion that is inconflict with the cost.The Technique for Order of Preference by Similarity toIdeal Solution (TOPSIS) is a multi-criteria decisionanalysis method, which was originally developed byHwang and Yoon in 1981 with further developments byYoon in 1987, and Hwang, Lai and Liu in 1993 [11].This method considers three types of attributes or criteria Qualitative benefit attributes/criteriaQuantitative benefit attributesCost attributes or criteriaIn this method, two artificial alternatives arehypothesized [12]:Ideal alternative: the one which has the best level forall attributes considered.Negative ideal alternative: the one which has theleast attribute values.TOPSIS selects the alternative that is the closest to theideal solution and farthest from negative ideal alternative.The idea of TOPSIS can be expressed in a series of steps[13-15].(1) Obtain performance data for n alternatives over kcriteria. Raw measurements are usuallystandardized; converting raw measures xij intostandardized measures sij.(2) Develop a set of importance weights wk, for eachof the criteria. The basis for these weights can beanything, but, usually, is ad hoc reflective ofrelative importance. Scale is not an issue ifstandardizing was accomplished in Step 1.(3) Identify the ideal alternative (extremeperformance on each criterion) s :(4) Identify the nadir alternative (reverse extremeperformance on each criterion) s¡:(5) Develop a distance measure over each criterionto both ideal (D ) and nadir (D¡).(6) For each alternative, determine a ratio R equal tothe distance to the nadir divided by the sum ofthe distance to the nadir and the distance to theideal, R D¡, D¡ D (7) Rank order alternatives by maximizing the ratioin Step 6.I.J. Information Engineering and Electronic Business, 2015, 6, 28-36
Identification of a Better Laptop with Conflicting Criteria Using TOPSISSpecificationWarrantySizeBattery lifeWith or without OSKeyboard and Touch e criteria are chosen based on the users requirementsand how they need the product to buy. Criteria are alsoreferred to as “attributes” or “goals”. Each DecisionMaking problem is associated with more than oneattribute or criteria. Criteria are generally known asparameters or characteristics. Alternatives can be viewedin different dimensions by means of using Criteria. Thecriteria that are considered in this research are describedin Table TERIASAMSUNGTable 1. List of AlternativesTable 3.User preference on different laptopsACERThe various alternatives, criteria which are collectedfrom different laptop vendors have been described inTable 1.The data collected from the laptop users are entered inthese following tables for each kind criteria andalternative. The user preference is described in Table 3.LGV. EXPERIMENTATIONData CollectionSONYIn this research, the new metric is defined from theresult of ranking the laptops by using the general TOPSISmethod in MCDM. The data set collected from the laptopusers and the students who belong to different instituteand different designation. The data set values will beapplied to the each step in TOPSIS and it produces theranking results. The new metric is defined from thatranking result. The sensitivity analysis is performed indifferent forms of result by changing the original valuesand the weights [13]. The weights are set as 1 and theweights are exchanged this will be applied in the TOPSISmethod and find the different ranking. The rank is getfrom the user to know the alternative which is belongs tothe rank. The new metric is defined by the Relativecloseness coefficient Relative Coefficient values to bereduced.TOSHIBA30Table 2. List of criteriaCostSpecification (RAM, Processor, graphics card, speed)WarrantySizeBattery lifeWith or without OSWeightKeyboard and Touch padWi-FiCopyright 2015 MECSI.J. Information Engineering and Electronic Business, 2015, 6, 28-36
Identification of a Better Laptop with Conflicting Criteria Using TOPSISThe experiment is conducted in MATLAP using thedataset described in Table 331The General TOPSIS method is performed bychanging all the weights of the criteria to 1. The result ofsensitivity analysis is shown in Table 4 when all theweights have changed to 1.VI. RESULTS AND DISCUSSIONIn order to identify the better laptop, based on variousconflicting criteria the MCDM method TOPSIS has beenapplied. In this research, to evaluate this application thewidely applied MCDM evaluation parameters such astime complexity, space complexity, sensitivity analysisand rank reversal are applied. The time complexity andspace complexity of this application are measureddirectly. The other evaluation parameters such assensitivity analysis and rank reversal are also applied toevaluate this MCDM application. In sensitivity analysis,all the criteria are assigned same weight and in anothermethod the weights are exchanged between thealternatives. This application is evaluated using the abovementioned MCDM evaluation parameters. The results aredescribed in the next sub section.Table 4. Weights for Sensitivity ry lifeWith or without OSWeightKeyboard and Touch padWi-FiAll the selected criteria are assigned weight 1. Theresults are described in Table 5.Table 5. Sensitivity analysis in TOPSIS when all the weight as 1SENSITIVITY ANALYSISALTERNATIVEA. Time and Space HIBASpace ComplexityB. Sensitivity AnalysisSensitivity analysis measures the impact on theoutcome by changing one or more key input values. It isused to investigate how sensitive the ranking ofalternatives when changes in weights and belief degreesfor certain attributes (Alinezhad & Amini, 2011). Theweights are change in two different methods and theefficiency is checked. Assign all attributes a weight value of 1, calledbasic weight.Sensitivity analysis on exchanging each criterionsweight with another criterions weight (Chen et al.,2014)Copyright 2015 982310510.80.6CriteriaThe better the time complexity of an algorithm is, thefaster the algorithm will carry out the work in practice.Apart from time complexity, space complexity is alsoimportant. This is essentially the number of memory cellswhich an algorithm needs. A good algorithm keeps thisnumber as small as possible. Space complexity taken forthe TOPSIS method is 1440 bytes.BEFORERANKTime complexity of an algorithm quantifies theamount of time taken by an algorithm for its execution. Itis commonly estimated by counting the number ofelementary operations performed by the algorithm, wherean elementary operation takes a fixed amount of time toperform. Thus the amount of time taken and the numberof elementary operations performed by an algorithmdiffers by a constant factor. The efficiency of thesealgorithms can be determined by the computational timerequired by the algorithm. Time complexity taken for theTOPSIS method is 0.061059 seconds.GENERAL TOPSISRANKTime Complexity Weights1111111110.40.20DellLenovo AppleHCLHP Samsung AcerLGSony ToshibaFig. 1. Sensitivity Analysis on changing weights to 1From the experimentation results, APPLE is the bestlaptop according to the selected criteria. The nextselected laptop is DELL with RCC of 0.6656. The leastpreferred laptop is LENOVO. To this experimentationresults sensitivity analysis is performed. It has beenI.J. Information Engineering and Electronic Business, 2015, 6, 28-36
32Identification of a Better Laptop with Conflicting Criteria Using TOPSIS10.80.6Criteriaperformed in two ways. In the first type all the weightsare changed into 1 and second method the weights areexchanged between the alternatives. To perform thesensitivity analysis the weights of the criteria areassigned the equal weight of 1. The results of sensitivityanalysis is represented in Fig.1In this sensitivity analysis, the ranking of thealternatives have not been changed. For the sameapplication is sensitivity analysis is conducted byexchanging weight as described in Table 6.0.40.2Table 6. Exchanging weight to perform Sensitivity 0.542094817325106HP Samsung AcerLGSony ToshibaTable 8. Changes in alternativesALTERNATIVESENSITIVITY ANALYSISGENERAL PPLEHCLHPSAMSUNGACERLGSONYTOSHIBAGENERAL TOPSISRANKALTERNATIVESENSITIVITY ANALYSISHCLThe Sensitivity Analysis is conducted in two differentways where the ranking result from TOPSIS method ischanging. In TOPSIS, all ranks are getting changed whenSensitivity analysis is conducted by changing all theweights to 1. Similarly, sensitivity analysis is conductedby exchanging weights between the criteria. In this case,all ranks are changed. The changes in the ranking orderof the alternative are described in Table 8.The sensitivity analysis to exchange each criterionweight with another criterion weight is conducted. Table7 shows the result of sensitivity analysis on exchangingweights. The weights are exchanged which is shown inTable 6. Then the sensitivity analysis is performed onTOPSIS method. The obtained result has been shown inTable 7. In this analysis, the ranking order of thealternatives is changed.Table 7. Sensitivity analysis when the weights are exchangedDell Lenovo AppleFig.2. Sensitivity Analysis on exchanging weightsRANKCOSTSPECIFICATIONWARRANTYSIZEBATTERY LIFEWITH ORWITHOUT OSWEIGHTKEYBOARD ANDTOUCH .40.3From the Table 7 it has been found that ranking orderof the alternatives is changed. The ranking order of thealternative APPLE has been changed from position 1 toposition 8. The ranking order of the alternative “DELL”has been shifted to 9. The least alternative “LENOVO”ranking order is changed into 4th position. The alteredranking order of alternatives has been described in Fig. 2.Copyright 2015 MECS0.20.10Dell Lenovo Apple HCLHP Samsung AcerLGSony ToshibaFig.3. Changes in alternativesI.J. Information Engineering and Electronic Business, 2015, 6, 28-36
Identification of a Better Laptop with Conflicting Criteria Using TOPSISIn this case, the most preferred alternative “APPLE”ranking order has been changed into sixth position. Thesecond preferred alternative “DELL” has been shiftedinto 7th position. The least preferred laptop “LENOVO”has been shifted to 4th position. These changes arerepresented in the graph depicted in Fig.3.To conduct the sensitivity analysis the value of thedata set has been changed. The change in dataset isdescribed in Table 9.Table 10. Changes in ranking order of the alternativesALTERNATIVESENSITIVITY ANALYSISSizeBattery lifeWith or without OSWeightKeyboard and Touch 879These changes are represented in graph depicted inFig.4.0.80.70.60.52.72.22.32.32.42.22.202.3Cri
evaluation metrics such as Time and Space Complexity, . Wi-Fi and Touch pad are considered as criteria to find the better laptop. It is difficult to select better laptop
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