Application of Heuristics and

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Application of Heuristics and Meta-Heuristics

• Scheduling
• Job Shop Scheduling
• Parallel Dedicated Machine (PDS1)
• Single machine minimize total tardiness
• Knapsack Problem
• Routing
• Traveling Salesman Problem
• Vehicle Routing Problem

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Application of Heuristics and Meta-Heuristics

• Mechanical Applications
• Simulated Annealing
• PC Board Layout (Cagan)
• Minimize footprint
• Constrained by heat transfer
• Genetic Algorithms
• Robotic path planning (Sturges and Rubin)

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Application of Heuristics and Meta-Heuristics

• Other Applications
• Title Submarine manoeuvring controllers
  optimisation using simulated annealing and
  genetic algorithms.
• Abstract This paper is concerned with non-linear
  controller parameter optimisation for the diving
  and heading motions of a submarine model. The
  structure of the non-linear controllers used for
  these manoeuvres is derived from Sliding Mode
  control theory for decoupled single input, single
  output systems. The performance of these
  controllers depends on key design parameters. In
  this comparative study the values of these
  controller parameters are optimised using three
  different optimisation techniques. These are
  simulated annealing, segmented simulated
  annealing and genetic algorithms. The search
  properties of these algorithms are defined and
  compared in terms of simulated time domain
  results, convergence and saturation properties.
  These results are used to show the advantages and
  disadvantages of each optimisation technique.

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Application of Heuristics and Meta-Heuristics
Other Applications Title Sampling schedule
design towards optimal drug monitoring for
individualizing therapy. Abstract We study the
individualization of therapy by simultaneously
taking into account the design of sampling
schedule and optimal therapeutic drug monitoring.
The sampling schedule design in this work is to
determine the number of samples, the sampling
times, the switching time from the loading to the
maintenance period, and the drug dosages. A
closed-loop control policy is employed to
determine the sampling schedule, and an advanced
stochastic global optimization algorithm, which
integrates the stochastic approximation and
simulated annealing techniques, is implemented to
search the optimal sampling schedule. A simulated
one-compartment model of intravenous theophylline
therapy is used to illustrate our method. This
method can be readily extended to multiple
compartment systems and allow incorporating other
criteria of drug control. While currently the
method is mainly of theoretical interest, it
offers a starting point for practical
applications and thus is hopefully of great value
for the clinically individualizing therapy in the
future.
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Application of Heuristics and Meta-Heuristics
Other Applications Title Distribution Network
Reconfiguration for Loss Reduction by Hybrid
Differential Evolution. Abstract This article
introduces a hybrid differential evolution (HDE)
method for dealing with optimal network
reconfiguration aiming at power loss reduction.
The network reconfiguration of distribution
systems is to recognize beneficial load transfers
so that the objective function composed of power
losses is minimized and the prescribed voltage
limits are satisfied. The proposed method
determines the proper system topology that
reduces the power loss according to a load
pattern. Mathematically, the problem of this
research is a nonlinear programming problem with
integer variables. This article presents a new
approach that employs the HDE algorithm with
integer variables to solve the problem. One
three-feeder distribution system from the
literature and one practical distribution network
of Taiwan Power Company are used to exemplify the
performance of the proposed method. Two other
methods, the genetic algorithm and the simulated
annealing, are also employed to solve the
problem. Numerical results show that the proposed
method is better than the other two methods.
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Application of Heuristics and Meta-Heuristics
Other Applications Title A comparative study
of markovian and variational image-matching
techniques in application to mammograms.
Abstract In this paper, we focus our interest
on the image-matching problem. This major problem
in Image Processing has received a considerable
attention in the last decade. However, contrarily
to other image-processing problems such as image
restoration, the image-matching problem have been
mainly tackled using a single approach based on
variational principles. In this paper, our
motivation is to investigate the feasibility of
another famous image-processing approach based on
Markov random fields (MRF). For that, we propose
a discrete and stochastic image-matching
framework which is equivalent to an usual
variational one and suitable for an MRF-based
approach. In this framework, we describe
multigrid implementations of two algorithms an
iterated conditional modes (ICM) and a simulated
annealing. We apply these algorithms for the
registration of mammograms and compare their
performances to those of an usual variational
algorithm. We come to the conclusion that
MRF-based techniques are optimization techniques
which are relevant for the mammogram application.
We also point out some of their specific
properties and mention interesting perspectives
offered by the markovian approach.
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Application of Heuristics and Meta-Heuristics
Other Applications Title Optimization of
Three-Phase Induction Motor Design Using
Simulated Annealing Algorithm. Abstract
Three-phase induction motors are designed to meet
various special requirements. Irrespective of
these requirements, the basic conditions to be
fulfilled are (1) The starting torque must be
high, and (2) Operating efficiency and power
factor must be as high as feasible. This article
discusses the formulation of design optimization
of three-phase induction motor as a nonlinear
multivariable programming problem to meet the
above requirements. Three different objective
functions were considered. The simulated
annealing algorithm was used to obtain an optimum
design. The algorithm was implemented on three
test motors and the results indicate that the
method has yielded a global optimum. The proposed
algorithm results are compared with the
conventional design results to select a suitable
optimal design of the induction motor. The
performance of the motor is found to improve with
application of this algorithm.
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Application of Heuristics and Meta-Heuristics
Other Applications Title A simulated
annealing applied for optimizing a voice-multihop
radio network. Abstract In this paper, we use
a variant of the simulated annealing algorithm
for solving the optimization of admission control
in a voice-multihop radio network problem. The
performance measure we consider is the call
blocking probabilities. This variant of the
simulated annealing uses constant temperature.
The standard clock simulation technique is used
to get estimates of performance measures of
several policies simultaneously. This results in
decreasing the required simulation time. The
simulation results indicate that this algorithm
can locate an optimal or a near optimal solution
quickly.
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Application of Heuristics and Meta-Heuristics
Believe it or not Title Structure, epitope
mapping, and docking simulation of a gibberellin
mimic peptide as a peptidyl mimotope for a
hydrophobic ligand.