Unconventional machining processes (communally named advanced or modern machining processes) are widely used by manufacturing industries. These advanced machining processes allow producing complex profiles and high quality-products. However, several process parameters should be optimized to achieve this end. In this paper, the optimization of process parameters of two conventional and four adva...

Bio inspiration is a branch of artificial simulation science that shows pervasive contributions to variety of engineering fields such as automate pattern recognition, systematic fault detection and applied optimization. In this paper, a new metaheuristic optimizing algorithm that is the simulation of “The Great Salmon Run” (TGSR) is developed. The obtained results imply on the acceptable perfor...

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algo...

Utilizing QFD in the process of manufacturing and service performing is confronted with an optimization problem called QFD decision-making problem (QFDDMP). Facing many customer constraints and requirements, and huge number of customers in the target market have made QFDDMP a complex planning problem. Achieving optimal solution by which the products satisfy customers with lowest costing budget ...

Liquid-liquid equilibrium (LLE) problems such as phase stability analysis, phase equilibrium calculations, chemical equilibrium calculations, binary interaction parameter identification of thermodynamic models and other problems of fluid characterization have been the core subject of many recent studies. This study introduces Cuckoo Search (CS), Firefly Algorithms (FA) and its variants as p...

Cuckoo Cycle is a recently proposed “memory-hard” computational Proof-of-Work (PoW) function designed to require a minimum amount of memory to compute efficiently. This paper describes two algorithms that use the sparsity of the Cuckoo Cycle graph to use less memory than both the initially hypothesized and updated proposed bounds for this proof-of-work function. The second algorithm presents a ...

Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to re...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

The contribution of this thesis is a mathematical analysis a high performance hashing scheme called cuckoo hashing when combined with two very simple and efficient classes of functions that we refer to as the multiplicative class and the linear class, respectively. We prove that cuckoo hashing tends to work badly with these classes. In order to show this, we investigate how the inner structure ...