The Experts below are selected from a list of 6 Experts worldwide ranked by ideXlab platform
Sanja Petrovic - One of the best experts on this subject based on the ideXlab platform.
-
decision support tool for multi objective job shop scheduling problems with linguistically Quantified decision functions
Decision Support Systems, 2007Co-Authors: Dobrila Petrovic, Alejandra Duenas, Sanja PetrovicAbstract:This paper presents a new tool for multi-objective job shop scheduling problems. The tool encompasses an interactive fuzzy multi-objective genetic algorithm (GA) which considers aspiration levels set by the decision maker (DM) for all the objectives. The GA's decision (fitness) function is defined as a measure of truth of a linguistically Quantified Statement, imprecisely specified by the DM using linguistic quantifiers such as most, few, etc., that refer to acceptable distances between the achieved objective values and the aspiration levels. The linguistic quantifiers are modelled using fuzzy sets. The developed tool is used to analyse and solve a real-world problem defined in collaboration with a pottery company. The tool provides a valuable support in performing various what-if analyses, for example, how changes of batch sizes, aspiration levels, linguistic quantifiers and the measure of acceptable distances affect the final schedule.
Dobrila Petrovic - One of the best experts on this subject based on the ideXlab platform.
-
decision support tool for multi objective job shop scheduling problems with linguistically Quantified decision functions
Decision Support Systems, 2007Co-Authors: Dobrila Petrovic, Alejandra Duenas, Sanja PetrovicAbstract:This paper presents a new tool for multi-objective job shop scheduling problems. The tool encompasses an interactive fuzzy multi-objective genetic algorithm (GA) which considers aspiration levels set by the decision maker (DM) for all the objectives. The GA's decision (fitness) function is defined as a measure of truth of a linguistically Quantified Statement, imprecisely specified by the DM using linguistic quantifiers such as most, few, etc., that refer to acceptable distances between the achieved objective values and the aspiration levels. The linguistic quantifiers are modelled using fuzzy sets. The developed tool is used to analyse and solve a real-world problem defined in collaboration with a pottery company. The tool provides a valuable support in performing various what-if analyses, for example, how changes of batch sizes, aspiration levels, linguistic quantifiers and the measure of acceptable distances affect the final schedule.
Alejandra Duenas - One of the best experts on this subject based on the ideXlab platform.
-
decision support tool for multi objective job shop scheduling problems with linguistically Quantified decision functions
Decision Support Systems, 2007Co-Authors: Dobrila Petrovic, Alejandra Duenas, Sanja PetrovicAbstract:This paper presents a new tool for multi-objective job shop scheduling problems. The tool encompasses an interactive fuzzy multi-objective genetic algorithm (GA) which considers aspiration levels set by the decision maker (DM) for all the objectives. The GA's decision (fitness) function is defined as a measure of truth of a linguistically Quantified Statement, imprecisely specified by the DM using linguistic quantifiers such as most, few, etc., that refer to acceptable distances between the achieved objective values and the aspiration levels. The linguistic quantifiers are modelled using fuzzy sets. The developed tool is used to analyse and solve a real-world problem defined in collaboration with a pottery company. The tool provides a valuable support in performing various what-if analyses, for example, how changes of batch sizes, aspiration levels, linguistic quantifiers and the measure of acceptable distances affect the final schedule.
Olivier Pivert - One of the best experts on this subject based on the ideXlab platform.
-
evaluation of flexible queries the Quantified Statement case
Technologies for constructing intelligent systems, 2002Co-Authors: Patrick Bosc, Ludovic Lietard, Olivier PivertAbstract:Many propositions to extend database management systems have been made in the last decade. Some of them aim to support a wider range of queries involving fuzzy predicates expressing preferences and this paper focuses on the evaluation of a particular subset of queries, namely those using fuzzy Quantified Statements. More precisely, we consider the queries calling on a partitioning where a linguistic quantifier appears in the set-oriented condition. This condition is expressed by a Quantified Statement of type "Q X are A" and its degree of truth is assumed to be computed via the Sugeno fuzzy integral. This paper proposes algorithms to evaluate such queries and the main objective is to reduce processing time by saving data access. Heuristics are integrated into the algorithms in order to conclude on the result without accessing all elements of the referential.
Patrick Bosc - One of the best experts on this subject based on the ideXlab platform.
-
evaluation of flexible queries the Quantified Statement case
Technologies for constructing intelligent systems, 2002Co-Authors: Patrick Bosc, Ludovic Lietard, Olivier PivertAbstract:Many propositions to extend database management systems have been made in the last decade. Some of them aim to support a wider range of queries involving fuzzy predicates expressing preferences and this paper focuses on the evaluation of a particular subset of queries, namely those using fuzzy Quantified Statements. More precisely, we consider the queries calling on a partitioning where a linguistic quantifier appears in the set-oriented condition. This condition is expressed by a Quantified Statement of type "Q X are A" and its degree of truth is assumed to be computed via the Sugeno fuzzy integral. This paper proposes algorithms to evaluate such queries and the main objective is to reduce processing time by saving data access. Heuristics are integrated into the algorithms in order to conclude on the result without accessing all elements of the referential.
