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Multi-objective optimisation in inventory planning with supplier selection (2017)
Journal Article
Turk, S., Özcan, E., & John, R. (2017). Multi-objective optimisation in inventory planning with supplier selection. Expert Systems with Applications, 78, doi:10.1016/j.eswa.2017.02.014

Supplier selection and inventory planning are critical and challenging tasks in Supply Chain Management. There are many studies on both topics and many solution techniques have been proposed dealing with each problem separately. In this study, we pre... Read More about Multi-objective optimisation in inventory planning with supplier selection.

Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation (2016)
Journal Article
Li, W., Özcan, E., & John, R. (2017). Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation. Renewable Energy, 105, doi:10.1016/j.renene.2016.12.022

Wind farm layout optimisation is a challenging real-world problem which requires the discovery of trade-off solutions considering a variety of conflicting criteria, such as minimisation of the land area usage and maximisation of energy production. Ho... Read More about Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation.

Evaluating decision making units under uncertainty using fuzzy multi-objective nonlinear programming (2016)
Journal Article
Zerafat Angiz, M., Nawawi, M., Khalid, R., Mustafa, A., Emrouznejad, A., John, R., & Kendall, G. (in press). Evaluating decision making units under uncertainty using fuzzy multi-objective nonlinear programming. Information Systems and Operational Research, 55(1), doi:10.1080/03155986.2016.1240944

This paper proposes a new method to evaluate Decision Making Units (DMUs) under uncertainty using fuzzy Data Envelopment Analysis (DEA). In the proposed multi-objective nonlinear programming methodology both the objective functions and the constraint... Read More about Evaluating decision making units under uncertainty using fuzzy multi-objective nonlinear programming.

Interval type–2 fuzzy decision making (2016)
Journal Article
Runkler, T., Coupland, S., & John, R. (2017). Interval type–2 fuzzy decision making. International Journal of Approximate Reasoning, 80, doi:10.1016/j.ijar.2016.09.007

This paper concerns itself with decision making under uncertainty and theconsideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature is limited in modelling decision making as there is no uncertainty in the membership function. We are... Read More about Interval type–2 fuzzy decision making.

Type-2 fuzzy alpha-cuts (2016)
Journal Article
Hamrawi, H., Coupland, S., & John, R. (2017). Type-2 fuzzy alpha-cuts. IEEE Transactions on Fuzzy Systems, 25(3), doi:10.1109/TFUZZ.2016.2574914

Type-2 fuzzy logic systems make use of type-2 fuzzy sets. To be able to deliver useful type-2 fuzzy logic applications we need to be able to perform meaningful operations on these sets. These operations should also be practically tractable. However,... Read More about Type-2 fuzzy alpha-cuts.

Learning of interval and general type-2 fuzzy logic systems using simulated annealing: theory and practice (2016)
Journal Article
Almaraashia, M., John, R., Hopgood, A., & Ahmadi, S. (2016). Learning of interval and general type-2 fuzzy logic systems using simulated annealing: theory and practice. Information Sciences, 360, doi:10.1016/j.ins.2016.03.047

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval... Read More about Learning of interval and general type-2 fuzzy logic systems using simulated annealing: theory and practice.

Quantification of R-Fuzzy sets (2016)
Journal Article
Singh Khuman, A., Yang, Y., & John, R. (2016). Quantification of R-Fuzzy sets. Expert Systems with Applications, 55, doi:10.1016/j.eswa.2016.02.010

The main aim of this paper is to connect R-Fuzzy sets and type-2 fuzzy sets, so as to provide a practical means to express complex uncertainty without the associated difficulty of a type-2 fuzzy set. The paper puts forward a significance measure, to... Read More about Quantification of R-Fuzzy sets.

Good Laboratory Practice for optimization research (2015)
Journal Article
Kendall, G., Bai, R., Blazewicz, J., De Causmaecker, P., Gendreau, M., John, R., …Yee, A. (2016). Good Laboratory Practice for optimization research. Journal of the Operational Research Society, 67(4), doi:10.1057/jors.2015.77

Good Laboratory Practice has been a part of non-clinical research for over 40 years yet. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin i... Read More about Good Laboratory Practice for optimization research.

Computing Nash equilibria and evolutionarily stable states of evolutionary games (2015)
Journal Article
Li, J., Kendall, G., & John, R. (in press). Computing Nash equilibria and evolutionarily stable states of evolutionary games. IEEE Transactions on Evolutionary Computation, 20(3), doi:10.1109/TEVC.2015.2490076

Stability analysis is an important research direction in evolutionary game theory. Evolutionarily stable states have a close relationship with Nash equilibria of repeated games, which are characterized by the folk theorem. When applying the folk theo... Read More about Computing Nash equilibria and evolutionarily stable states of evolutionary games.

Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey (2015)
Journal Article
Deveci, M., Çetin Demirel, N., John, R., & Özcan, E. (in press). Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey. Journal of Natural Gas Science and Engineering, 27(2), doi:10.1016/j.jngse.2015.09.004

The problem of choosing the best location for CO2 storage is a crucial and challenging multi-criteria decision problem for some companies. This study compares the performance of three fuzzy-based multi-criteria decision making (MCDM) methods, includi... Read More about Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey.

Interval-valued fuzzy decision trees with optimal neighbourhood perimeter (2014)
Journal Article
Lertworaprachaya, Y., Yang, Y., & John, R. (2014). Interval-valued fuzzy decision trees with optimal neighbourhood perimeter. Applied Soft Computing, 24, doi:10.1016/j.asoc.2014.08.060

This research proposes a new model for constructing decision trees using interval-valued fuzzy membership values. Most existing fuzzy decision trees do not consider the uncertainty associated with their membership values, however, precise values of f... Read More about Interval-valued fuzzy decision trees with optimal neighbourhood perimeter.

Uncertainty representation of grey numbers and grey sets (2014)
Journal Article
Yang, Y., Liu, S., & John, R. (2014). Uncertainty representation of grey numbers and grey sets. IEEE Transactions on Cybernetics, 44(9), doi:10.1109/TCYB.2013.2288731

In the literature there is a presumption that a grey set and an interval-valued fuzzy set are equivalent. This presumption ignores the existence of discrete components in a grey number. In this paper new measurements of uncertainties of grey numbers... Read More about Uncertainty representation of grey numbers and grey sets.

Grey sets and greyness (2012)
Journal Article
Yang, Y., & John, R. (2012). Grey sets and greyness. Information Sciences, 185(1), doi:10.1016/j.ins.2011.09.029

This paper discusses the application of grey numbers for uncertainty representation. It highlights the difference between grey sets and interval-valued fuzzy sets, and investigates the degree of greyness for grey sets. It facilitates the representati... Read More about Grey sets and greyness.

Interval type-2 fuzzy modelling and stochastic search for real-world inventory management (2012)
Journal Article
Miller, S., Gongora, M., Garibaldi, J., & John, R. (2012). Interval type-2 fuzzy modelling and stochastic search for real-world inventory management. Soft Computing, 16(8), doi:10.1007/s00500-012-0848-y

Real-world systems present a variety of challenges to the modeller, not least of which is the problem of uncertainty inherent in their operation. In this research, an interval type-2 fuzzy model is applied to a real-world problem, the goal being to d... Read More about Interval type-2 fuzzy modelling and stochastic search for real-world inventory management.

Intuitionistic fuzzy similarity measures and their role in classification
Journal Article
Baccour, L., Alimi, A., & John, R. Intuitionistic fuzzy similarity measures and their role in classification. Journal of Intelligent Systems, 25(2), doi:10.1515/jisys-2015-0086

We present some similarity and distance measures between intuitionistic fuzzy sets (IFSs). Thus, we propose two semi-metric distance measures between IFSs. The measures are applied to classification of shapes and handwritten Arabic sentences describe... Read More about Intuitionistic fuzzy similarity measures and their role in classification.


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