In robot odometry and SLAM applications the real trajectory is estimated incrementally. This produces an accumulation of errors which gives raise to a drift in the trajectory. When revisiting a previous position this drift becomes observable and thus it can be corrected by applying loop closing techniques. Ultimately a loop closing process leads to an optimisation problem where new constraints ...

In biomechanics, musculoskeletal models are typically redundant. This situation is referred to as the distribution problem. Often, static, non-linear optimisation methods of the form "min: phi(f) subject to mechanical and muscular constraints" have been used to extract a unique set of muscle forces. Here, we present a method for validating this class of non-linear optimisation approaches where ...

Membrane computing models (also known as P Systems) that solve optimisation problems using genetic algorithms, ant colony optimisation, quantum-inspired evolutionary algorithm and particle swarm optimisation have been defined and are efficiently used in several applications. This paper describes the design of a variant of the existing Distributed P system (dP system) that is augmented with new ...

Since the establishment of the area of search-based software engineering, a wide range of optimisation techniques have been applied to automate various stages of software design and development. Architecture optimisation is one of the aspects that has been automated with methods like genetic algorithms, local search, and ant colony optimisation. A key challenge with all of these approaches is t...

We present a model hierarchy multilevel optimisation approach to solve an optimal boundary control problem in glass manufacturing. The process is modelled by radiative heat transfer and formulated as an optimal control problem restricted by partial differential algebraic equations (PDAE) and additional control constraints. We consider a sequence of model approximations given by space-time depen...

This paper describes the initial results of a new form of evolutionary system specifically designed for time series modeling. The system combines a grammaticallybased Genetic Programming system with various optimisation techniques. The system uses the evolutionary system to construct the structure of equations and optimisation techniques to essentially fill in the details. Three forms of optimi...

Femtocells are small base stations that provide radio coverage for mobile devices in homes or office areas. In this paper, we consider the optimisation of a number of femtocells that provide joint coverage in enterprise environments. In such an environment, femtocells should minimise coverage overlap and coverage holes and ensure a balanced traffic workload among them. We use statistical verifi...

1 Abstract In this paper a procedure for global optimisation is presented. The procedure combines on two methods, viz. the Multipoint Approximation based on Response Surface fitting (MARS) Method and a global optimisation method. The MARS method is based on the approximation concepts according to which the original minimization problem is replaced with a succession of simpler ones formulated fo...

Since information in engineering design problems can be both quantitative (Q T ) and qualitative (Q L ) in nature, combining both types of information can result in more realistic solution for real world optimisation problems. However, most of the approaches reported in literature are incapable of conducting optimisation search in such mixed environment. Therefore this paper proposes a mathemat...

The problem of cooperation of model predictive control (MPC) algorithm with nonlinear (local) steady-state optimisation is considered. It is important when dynamics of disturbances is comparable with dynamics of the process, thus when application of a classical multi-layer approach may be not efficient. The case concerns a situation when a reliable steady-state process model is nonlinear, often...