Liana Napalkova

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This paper describes a system developed to assist in model-based training of minimally invasive, laparoscopic procedures. The key factor motivating the development of the device called CAST (Computer-Assisted Surgical Trainer) is the need to improve the state-of-the-art in teaching laparoscopy, and ultimately achieve better surgical outcomes. CAST's design(More)
This paper focuses on the development of simulation-based environment for multi-echelon cyclic planning and optimisation in the product maturity phase. It is based on integration of analytical and simulation techniques. Analytical techniques are used to obtain initial planning decisions under conditions of stochastic demand and lead time, whereas simulation(More)
This paper develops a multi-objective simulation-based genetic algorithm (MOSGA) for multi-echelon supply chain cyclic planning and optimisation. The problem involves a search in high dimensional space with different ranges for decision variables scales, multiple objectives and problem specific constraints, such as power-of-two and nested/inverted-nested(More)
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright The papers in(More)
The paper describes the algorithm, which is developed to solve scheduling tasks in Flexible Manufacturing Systems. The algorithm is a combination of Genetic Algorithm and Coloured Petri Nets. It is proposed to use Coloured Petri Nets to tackle the encoding problem in Genetic Algorithm. The objective is to minimize the total make-span subject to different(More)
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