Multicriteria ranking using weights which minimize the score range

Various schemes have been proposed for generating a set of non-subjective weights when aggregating multiple criteria for the purposes of ranking or selecting alternatives. The maximin approach chooses the weights which maximise the lowest score (assuming there is an upper bound to scores). This is equivalent to finding the weights which minimize the maximum deviation, or range, between the worst and best scores (minimax). At first glance this seems to be an equitable way of apportioning weight, and the Rawlsian theory of justice has been cited in its support.We draw a distinction between using the maximin rule for the purpose of assessing performance, and using it for allocating resources amongst the alternatives. We demonstrate that it has a number of drawbacks which make it inappropriate for the assessment of performance. Specifically, it is tantamount to allowing the worst performers to decide the worth of the criteria so as to maximise their overall score. Furthermore, when making a selection from a list of alternatives, the final choice is highly sensitive to the removal or inclusion of alternatives whose performance is so poor that they are clearly irrelevant to the choice at hand

On multimodality of obnoxious faclity location models

Obnoxious single facility location models are models that have the aim to find the best location for an undesired facility. Undesired is usually expressed in relation to the so-called demand points that represent locations hindered by the facility. Because obnoxious facility location models as a rule are multimodal, the standard techniques of convex analysis used for locating desirable facilities in the plane may be trapped in local optima instead of the desired global optimum. It is assumed that having more optima coincides with being harder to solve. In this thesis the multimodality of obnoxious single facility location models is investigated in order to know which models are challenging problems in facility location problems and which are suitable for site selection. Selected for this are the obnoxious facility models that appear to be most important in literature. These are the maximin model, that maximizes the minimum distance from demand point to the obnoxious facility, the maxisum model, that maximizes the sum of distance from the demand points to the facility and the minisum model, that minimizes the sum of damage of the facility to the demand points. All models are measured with the Euclidean distances and some models also with the rectilinear distance metric. Furthermore a suitable algorithm is selected for testing multimodality. Of the tested algorithms in this thesis, Multistart is most appropriate. A small numerical experiment shows that Maximin models have on average the most optima, of which the model locating an obnoxious linesegment has the most. Maximin models have few optima and are thus not very hard to solve. From the Minisum models, the models that have the most optima are models that take wind into account. In general can be said that the generic models have less optima than the weighted versions. Models that are measured with the rectilinear norm do have more solutions than the same models measured with the Euclidean norm. This can be explained for the maximin models in the numerical example because the shape of the norm coincides with a bound of the feasible area, so not all solutions are different optima. The difference found in number of optima of the Maxisum and Minisum can not be explained by this phenomenon

A New Model for the Secondary Goal in DEA

The purpose of the current paper is to propose a new model for the secondary goal in DEA by introducing secondary objective function. The proposed new model minimizes the average of the absolute deviations of data points from their median. Similar problem is studied in a related model by Liang et al. (2008), which minimizes the average of the absolute deviations of data points from their mean. By using two well known data sets, which are also used by Liang et al.(2008), and Greene (1990)  we compare the results of the proposed new model and several other models

Multiple criteria decision making in application layer networks

This work is concerned with the conduct of MCDM by intelligent agents trading commodities in ALNs. These agents consider trustworthiness in their course of negotiation and select offers with respect to product price and seller reputation. --Grid Computing

A Multicriteria Framework for Benchmarking Sustainability Performance of Organizations

Sustainability involves meeting the needs of present generation without compromising the requirements of future generations. It involves focus on three main pillars: economic, environmental and social for realizing overall performance. Sustainability assessment is very essential for business organizations to improve their competition capacity. Majority of them are moving towards sustainability practices for corporate progress and improving the business appearance for long term effectiveness, thereby receiving economic benefits as well. In this thesis, we propose a multi-criteria framework for benchmarking sustainability performance of organizations. The indicators for evaluation are obtained using Sustainalytics database. Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and Data Envelopment Analysis (DEA) are used to generate sustainability rankings and determine targets for improvement. The proposed techniques are applied to evaluate performance of 24 companies in two major sectors: manufacturing and service. The selected companies come from the Canadian market. The results of TOPSIS study show manufacturing sector to be doing better than the service sector with average Relative Closeness (Ci) values as 0.5 and 0.36 respectively. The DEA method identified 10 inefficient companies in each sector and provided targets for improvement. Future work can involve integration of financial Key Performance Indicators (KPIs), cross-sector investigation and involvement of Multi-Criteria Decision Making (MCDM) techniques such as Analytic Hierarchy Process (AHP) for criteria weighting in the proposed study