We consider revenue management problems when customers choose among the offered products according to the Markov chain choice model. In this choice model, a customer arrives into the system to purchase a particular product. If this product is available for purchase, then the customer purchases it. Otherwise, the customer transitions to another product or to the no purchase option, until she rea...

Traditional animation by key frame techniques takes animators lots of time and vigour to model and simulate behaviours of crowds. For solving this problem, this paper presents a novel group animation generation approach based on population-based optimization algorithms. It is mainly divided into two parts. First, it puts forward a role modelling approach based on dynamic selfadaptive genetic al...

In this paper, we develop a finite horizon model predictive control algorithm which is robust to modelling uncertainties. A moving average system matrix is constructed to capture modelling uncertainties and facilitate the future output prediction. The paper is mainly focused on the step tracking problem. Using linear matrix inequality techniques, the design is converted into a semi-definite opt...

In this contribution, we summarize the state of the art of the inductive modelling world wide. Recently, there is a trend to utilize evolutionary algorithms for optimization of inductive models. Also some new approaches in feature selection using inductive modelling, model validation, ensembles of inductive models, etc. are to be described.

Operations Research present state and future trends are analyzed from the Fuzzy-Sets-based methodologies point of view. Then, in a more particular perspective, some speciic topics of Fuzzy-Sets-based models in Operations Research, such as fuzzy optimization, preference modelling, linguistic modelling and decision models, as well as some other well known Operations Research speciic topics, are a...

We argue for the benefits of relations over functions for modelling programs, and even more so for modelling specifications. To support this argument, we present an extended case study for a class of optimization problems, deriving efficient functional programs from concise relational specifications.

This paper introduces the use of dynamic stochastic optimisation pension fund management. The design of such products involves econometric modelling, economic scenario generation, generic methods of solving optimization problems and modelling of required risk tolerances. In nearly all the historical backtests using data over roughly the past decade the system described (with transactions costs ...

Mathematical optimization models are commonly implemented by specifying them in a high-level declarative modelling language. These languages allow specifying the overall model structure separately from the actual numerical values that are needed to form a specific instance of the model. The existing modelling languages are typically interpreted when the model is generated. In largescale linear ...