The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the multi objective optimization with the criteria of makespan minimization and minimization of total weighted flow time for the flow shop scheduling problem. The n-job mmachine problem is known to be NP hard problem, several meta heuristics have been applied so far in the...

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentia...

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentia...

abstract one of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. so, simulation and forecasting models such as artificial neural networks (anns) are commonly used for simulation and predi...

introduction this study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. the medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. by analyzing this information, the best diagnostic parameters among the available parameters are selected and ...

The concern about customer satisfaction and transportation cost in the business environment has spurred an interest in designing a flexible logistics network. This paper proposes a multi-delivery path closed-loop supply chain network to find not only the most cost efficient network design but also the best path to deliver the products to customers. To tackle with such an NP-hard problem an Arti...

This paper presents a new approach with artificial immune system algorithm to solve the profit based unit commitment problem. The objective of this work is to find the optimal generation scheduling and to maximize the profit of generation companies (Gencos) when subjected to various constraints such as power balance, spinning reserve, minimum up/down time and ramp rate limits. The proposed hybr...

Based on analyzing natural immune phenomena and utilizing performances of the existing artificial neural networks, a novel network model (artificial neural network based on immunity-ANNI) is proposed which integrates the immune mechanism and the function of neural information processing. The learning algorithm of ANNI contains the method of selecting an excitation function and an adaptive algor...

An immune system without tissue is like evolution without genes. Something very important is missing. Here we present the novel concept of tissue for artificial immune systems. Much like the genetic representation of genetic algorithms, tissue provides an interface between problem and immune algorithm. Two tissue-growing algorithms are presented with experimental results illustrating their abil...

In this paper, we show the functional similarities between Meta-heuristics and the aspects of the science of life (biology): (a) Meta-heuristics based on gene transfer: Genetic algorithms (natural evolution of genes in an organic population), Transgenic Algorithm (transfers of genetic material to another cell that is not descending); (b) Meta-heuristics based on interactions among individual in...