Researchers laid the foundation of evolutionary algorithms in the late 60s and since then, heuristic algorithms have been widely applied to several complex scheduling and sequencing problems during the recent studies. In this paper, memetic algorithm (MA), genetic algorithm (GA) and simulated annealing (SA) are applied to a complex sequencing problem. The problem under study concerns about sequ...

The finishing train of a hot strip mill has been modelled by using a constant volume element model. The accuracy of the model has been increased by using an Artificial Neural Network (ANN). A non-linear Rank Based Genetic Algorithm has been developed for the optimization of the work roll profiles in the finishing stands of the simulated hot strip mill. It has been compared with eight other expe...

in this paper, a stochastic multi-depot multi-objective vehicle routing problem (vrp) is studied. based on observations in real-world problems, we develop an aspect of the problem, such as stochastic availability of routes. to solve the problem in this situation, a two-objective mathematical model is developed, in which the related objective functions are: (1) minimizing transportation costs an...

This paper addresses the single machine early/ tardy problem with unrestricted common due date and sequence-dependent setup times. Two algorithms are introduced to reach near-optimum solutions: the SAPT, a heuristic tailored for the problem, and a simulated annealing (SA) algorithm. It will be shown that SA provides solutions with slightly better quality; however, SAPT requires much less comput...

In this study, for the loads supplied by three thermic plants, power of thermic plants, supplying the minimum values of the cost of energy used for an hour, have been found with Simulated Annealing (SA) which is a metaheuristic optimasition method. Firstly solution have been found with classical Lagrange Method. Later solution have also been found with SA algorithm. Solutions found with two dif...

This paper presents a Simulated Annealing (SA) algorithm for solving the Environmental/Economic Dispatch Problem (EED). This problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are maximum and minimum limits of power generation while the equality constrai...

In order to further enhance the performance of syntax parsing, for the shortcomings of hidden Markov model (HMM) in the parameter optimization, an improved syntax parsing method based on adaptive genetic annealing and HMM was presented. First, an adaptive hybrid genetic annealing algorithm was adopted to optimize HMM initial parameters. Second, the improved HMM was trained by Baum Welch algorit...

Particle swarm optimization (PSO) algorithm is simple stochastic global optimization technique, but it exists unbalanced global and local search ability, slow convergence speed and solving accuracy. An improved simulated annealing (ISAM) algorithm is introduced into the PSO algorithm with crossover and Gauss mutation to propose an improved PSO (ISAMPSO) algorithm based on the mutation operator ...

The problem of scheduling n jobs with a large common due date on a single machine is addressed. The objective is to minimize the jobs’ total earliness and tardiness. In this paper, sequence-dependent setup times are considered, which makes the problem NP-Hard. Therefore, exact algorithms are very unlikely to optimally solve large problems within reasonable computational time. A Simulated Anneal...

In this paper, six different approaches using genetic algorithms (GA) and/or simulated annealing (SA) with improved bottom left (I-BL) algorithm [1] were applied for solution of two dimensional non-guillotine cutting problems. As examples, test problems including 29 individual rectangular pieces were used [2]. Performances of hybrid approaches on solutions of cutting problems were compared. Due...