Presentation on theme: "Application of Heuristics and Meta-Heuristics Scheduling: Job Shop Scheduling Parallel Dedicated Machine (PDS1) Single machine minimize total tardiness."— Presentation transcript:
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
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)
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.
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.
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.
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.
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.
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.
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.
Application of Heuristics and Meta-Heuristics Let’s hear from Option C term project students