In the last decade job shop scheduling problems have been subject to intensive research due to their multiple applications. Job shop scheduling is known as a strongly NPcomplete problem. In the job shop scheduling problems, processing times and due dates are very dynamically due to both human and machine resource factors. Fuzzy sets are used to model the uncertain processing times and due dates...

This paper presents a Heuristic Genetic Algorithm (HGA) for optimizing two dimensional (2D) arbitrary sized heterogeneous box packing into a container, by considering practical constraints facing in the shipment container loading industries. Objective of this research is to pack heterogeneous boxes of varying length, width and constant height into a container of standard dimension, without viol...

A type II line balancing problem with multiple workers in workstations (mALBP-II) is considered given a total number of workers, group and tasks into so as to minimize cycle time. Different from the manufacturing environment where traditional assembly (ALBP) rises, manual or semimanual enjoys much higher flexibility allowing perform same set on workpieces workstation parallel. The freedom speci...

This paper provides a corrected formulation to the mixed integer programming model proposed by Aydogan et al. (2012) [1]. They proposed a genetic algorithm to learn fuzzy rules for a fuzzy rule-based classification system and developed a Mixed Integer Programming model (MIP) to prune the generated rules by selecting the best set of rules to maximize predictive accuracy. However, their proposed ...

Ad hoc networks face serious security threat due to its inherent weaknesses. Intrusion detection is crucial technology in protecting the security of Ad hoc networks. Recently, Intrusion Detection Systems (IDS) face open issues, such as how to make use of intrusion detection technologies to excavate normal/abnormal behaviors from a lot of initialized data and dig out invasion models later for in...

A genetic algorithm (GA) is a robust problem-solving method based on natural selection. Hardware's speed advantage and its ability to parallelize ooer great rewards to genetic algorithms. Speedups of 1{3 orders of magnitude have been observed when frequently used software routines were implemented in hardware by way of reprogrammable eld-pro-grammable gate arrays (FPGAs). Reprogrammability is e...

Redundancy-allocation problem i.e. RAP is among the reliability optimization problems which make use of non-linear programming method to improve complex system. The objective this research paper through application Genetic Algorithm GA and Hybrid & Particle Swarm Optimization (H-GAPSO) on a RAP. Certain shortcomings have been seen when results are obtained by single algorithms. In order get...

Recently, genetic algorithms (GAs) and their hybrids have achieved great success in solving difficult combinatorial optimization problems. In this paper, the issues related to the performance of the genetic search in the context of the grey pattern problem (GPP) are discussed. The main attention is paid to the investigation of the solution recombination, i.e., crossover operators which play an ...

This paper considers the Bicriteria Network Design Problem (bNDP) with the two conflicting objectives of minimizing cost and maximizing flow. Network design problems where even one flow measure be maximized, are often NP-hard problems. But, in real-life applications, it is often the case that the network to be built is required to optimize multi-criteria simultaneously. Thus the calculation of ...

We propose a Hybrid Genetic Algorithm (HGA) for a combinatorial optimization problem, motivated by, and a simplification of, a TV Self-promotion Assignment Problem. The problem consists of, given the weekly self-promotion space (a set of TV breaks with known duration) and a set of products to promote, to assign the products to the breaks in the “best” possible way. The objective is to maximize ...