In this paper, we considered solving approaches to flexible job shop problems. Makespan is not a good evaluation criterion with overlapping in operations assumption. Accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. As overlapping in operations is a practical assumption in chemical, petrochemical, and gla...

GA genetic algorithm HGA hybrid genetic algorithm SA simulated annealing algorithm ACO ant colony optimization TS tabu search IA immune algorithm GDA great deluge algorithm CEA cellular evolutionary approach NN neural network NFT near feasible threshold UGF universal generating function MSS multi-state system RB/i/j recovery block architecture that can tolerate i hardware and j software faults ...

This paper presents a genetic algorithm (GA) search method in order to obtain better circuit implementation of the mixed polarity Reed-Muller functions. By combining global searching ability of genetic algorithm and local searching ability of simulated annealing, the proposed GA method could achieve fast convergence. It differs to traditional genetic algorithm, in which the proposed GA forms an...

  The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...

integrated production-distribution planning (pdp) is one of the most important approaches in supply chain networks. we consider a supply chain network (scn) to consist of multi suppliers, plants, distribution centers (dcs), and retailers. a bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...

Template learning has potential application in several areas of Cellular Neural Network research, including texture recognition, pattern detection and so on. In this letter, a recently-developed algorithm called Adaptive Simulated Annealing is investigated for learning CNN templates, as a superior alternative to the Genetic Algorithm. key words: adaptive simulated annealing, cellular neural net...

Boltzmann evolutionary algorithms and their embedded selection mechanisms are traditionally employed to prolong search. After a brief introduction, a precursor called simulated annealing is outlined. A prominent type of Boltzmann evolutionary algorithm called parallel recombinative simulated annealing is then covered in depth. A proof of global convergence for this type of algorithm is illustra...

The simulated annealing algorithm has been introduced into the broadcast routing of wireless sensor network so as to reduce the length and energy of broadcast path. However, its new solution is generated by randomly exchanging the location of two sensor nodes of broadcast path. Though the simulated annealing algorithm is better than 2-opt algorithm, its method of generating new solution has sti...

This paper presents a new method to pack convex polygons into bins (the nesting problem). To do this polygons are placed in rows within bins using a metaheuristic algorithm (simulated annealing) and by utilising the No Fit Polygon. We show that simulated annealing out performs hill climbing. The nesting algorithm is described in detail, along with various aspects that have been incorporated in ...

We propose a variant of the Simulated Annealing method for optimization in the multivariate analysis of diierentiable functions. The method uses the Hybrid Monte Carlo algorithm for the proposal of new conngurations. We show how this choice can improve the performance of simulated annealing methods by allowing much faster annealing schedules.