Using ELECTRE TRI outranking method to sort MOMILP nondominated solutions

Several interactive methods exist to identify nondominated solutions in a Multiple Objective Mixed Integer Linear Program. But what if the Decision Maker is also interested in sorting those solutions (assigning them to pre-established ordinal categories)? We propose an interactive "branch-and-bound like" technique to progressively build the nondominated set, combined with ELECTRE TRI method (Pessimistic procedure) to sort identified nondominated solutions. A disaggregation approach is considered in order to avoid direct definition of all ELECTRE TRI preference parameters. Weight-importance coefficients are inferred and category reference profiles are determined based on assignment examples provided by the Decision Maker. A computation tool was developed with a twofold purpose: support the Decision Maker involved in a decision process and provide a test bed for research purposes.http://www.sciencedirect.com/science/article/B6VCT-48GF3RT-B/1/55841cf788557c60dac156a4e7b1890

A novel sorting method topsis-sort: an applicaiton for tehran environmental quality evaluation

Many real-life problems are multi-objective by nature that requires evaluation of more than one criterion, therefore MCDM has become an important issue. In recent years, many MCDM methods have been developed; the existing approaches have been improved and extended. Multi criteria decision analysis has been regarded as a suitable set of methods to perform sustainability evaluations. Among numerous MCDM methods developed to solve real-life decision problems, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily in diverse application areas. In this paper, a novel sorting method (TOPSIS-Sort) based on the classic TOPSIS method is presented. In the TOPSIS-Sort approach an outranking relation is used for sorting purposes. The proposed approach uses characteristic profiles for defining the classes and outranking relation as the preference model. Application of the proposed approach is demonstrated by classifying 22 districts of Tehran into five classes (but none of the districts fits into Classes 4 and 5), representing areas with different levels of environmental quality. An analysis and assessment of the environmental conditions in Tehran helps to identify the districts with the poor environmental quality. Priority should be given to these areas to maintain and improve the quality of environment. The results obtained by the TOPSIS-Sort give credence to its success, because the results of sorting con firm our and specialists’ evaluation of the districts. This research provides appropriate results with respect to the development of sorting models in the form of outranking relations. The model, proposed by this study, is applicable to the other outranking methods such as ELECTRE, PROMETHEE, etc

Cognitive mapping and multi-criteria analysis for decision aiding: an application to the design of an electric vehicle sharing service

The paper presents a model for the design of an electric car sharing service for the city of Milano. Several options of service configurations have been analysed and evaluated according to indicators, to measure the performance of such options in respect to relevant dimensions (i.e., economic and financial costs and revenues, mobility, social benefits, environmental effects). We set up a multicriteria decision analysis, structured by means of cognitive maps. Causal networks to estimate the effects of the options have been identified and instantiated by means of simulation techniques and other qualitative and quantitative models. The focus of the paper is on the development and use of the causal maps and their integration with a multicriteria method. The use of cognitive maps allowed to capture the multiple values of the problem and the value trees of stakeholders objectives. The proposed method can be useful in general for design and planning of mobility service, especially at a strategic level

Robust ordinal regression for value functions handling interacting criteria

International audienceWe present a new method called UTAGMS–INT for ranking a finite set of alternatives evaluated on multiple criteria. It belongs to the family of Robust Ordinal Regression (ROR) methods which build a set of preference models compatible with preference information elicited by the Decision Maker (DM). The preference model used by UTAGMS–INT is a general additive value function augmented by two types of components corresponding to ‘‘bonus’’ or ‘‘penalty’’ values for positively or negatively interacting pairs of criteria, respectively. When calculating value of a particular alternative, a bonus is added to the additive component of the value function if a given pair of criteria is in a positive synergy for performances of this alternative on the two criteria. Similarly, a penalty is subtracted from the additive component of the value function if a given pair of criteria is in a negative synergy for performances of the considered alternative on the two criteria. The preference information elicited by the DM is composed of pairwise comparisons of some reference alternatives, as well as of comparisons of some pairs of reference alternatives with respect to intensity of preference, either comprehensively or on a particular criterion. In UTAGMS–INT, ROR starts with identification of pairs of interacting criteria for given preference information by solving a mixed-integer linear program. Once the interacting pairs are validated by the DM, ROR continues calculations with the whole set of compatible value functions handling the interacting criteria, to get necessary and possible preference relations in the considered set of alternatives. A single representative value function can be calculated to attribute specific scores to alternatives. It also gives values to bonuses and penalties. UTAGMS–INT handles quite general interactions among criteria and provides an interesting alternative to the Choquet integral

Using SSM for structuring decision support in urban energy planning

This paper describes the use of Soft Systems Methodology (SSM) as a tool for problem structuring, which is the first phase encompassed in a methodological approach currently under development to provide decision support based on Multi‐Criteria Decision Analysis (MCDA) in energy planning problems in an urban context. In order to apply the methodology to a real‐world problem, a medium sized Portuguese city has been chosen as the decision setting. SSM is used for characterizing as precisely as possible the decision problem context, identifying the main stakeholders and their relations, and discerning the relevant criteria at stake for each one. Future work directions based on this phase are also envisaged. Santrauka Straipsnyje aprašoma operacinės sistemos metodologija (OSM), kuri bus taikoma kaip daugiakriterinės analizės metodais pagrįsta sprendimų paramos sistema miesto energetikos planavimo problemoms spręsti. Siekiant metodologiją pritaikyti realiame gyvenime, eksperimentui buvo parinktas vidutinio dydžio Portugalijos miestas. Operacines sistemos metodologija taikyta kuo tiksliau nustatant pagrindines problemas, identifikuojant pagrindines suinteresuotas šalis ir jų santykius, nustatant vienas kitam įtaka darančius rodiklius. Numatytos būsimos darbo kryptys. First published online: 10 Feb 2011 Reikšminiai žodžiai: operacinė sistemos metodologija, daugiakriterinė sprendimų analizė, miesto energetikos planavima