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This article presents a review of the use of optimisation models for pedestrian evacuation and design problems.
In particular, we have discussed the use of optimisation algorithms such as simulated annealing and of soft computing-based clustering algorithms including fuzzy c-means, rough c-means, and combined fuzzy-rough c-means approaches in this context.
Key elements of the grassroots component are Multiple Utilities, Heat Transfer Area considerations, additional design tools beyond the Pinch Design Method, forbidden matches and an introduction to the use of optimisation for heat exchanger network design.
The use of optimisation to find efficient protected area solutions is motivated by a belief that such solutions have relatively higher social acceptability and therefore stand a greater chance of being implemented (e.g. Fernandes et al., 2005; Game et al., 2011).
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Due to the convexity properties of the model, global optimal solutions are achieved through the standard branch-and-bound procedure with commercial optimisation solvers, but use of this optimisation framework is limited to small-medium scale networks due to NP-hardness.
The solid model designed was enhanced by use of an optimisation system.
This method consists in designing state-feedback control with the use of BMI optimisation.
In many cases, to solve these problems it is necessary the use of emergent optimisation algorithms.
Various selection strategies have been applied in the past and one approach that has proved effective is the use of combinatorial optimisation methods.
The use of generic optimisation techniques such as simulated annealing and soft computing-based clustering algorithms founded on fuzzy and rough set ideas to formulate colour quantisation algorithms is discussed.
The design of safety critical systems that meet dependability (e.g. safety and reliability) criteria is a hard combinatorial problem and there is a need for tools that make use of systematic optimisation algorithms to provide technological assistance.
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