This paper addresses parallel machine scheduling problems with fuzzy processing times. A robust genetic algorithm (GA) approach embedded in a simulationmodel is proposed tominimize the maximum completion time (makespan). The results are compared with those obtained by using the ‘‘longest processing time’’ rule (LPT), which is known as the most appropriate dispatching rule for such problems. Thi...

Genetic Algorithm (GA) is known as method to solve Traveling Salesman Problem (TSP). However, GA needs amount of time for finding approximate solution. Thus, this study proposes Genetic Algorithm with Virus Infection (GAVI). GAVI algorithm is using Virus Theory of Evolution (VTE) to be based on Genetic Algorithm (GA). GA can evolve by natural selection, while VTE can evolve by virus infection. ...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

This paper delves into the scheduling of two-machine flow-shop problem with step-learning, a scenario in which job processing times decrease if they commence after their learning dates. The objective is to optimize resource allocation and task sequencing ensure efficient time utilization timely completion all jobs, also known as makespan. identified established NP-hard due its reduction single ...

Use of heuristic methods is common to find the solutions to the optimization problems for scientific and real time. Problems such as Travelling Salesman (TSP) require more accurate solution which is tried by various optimization methods. Research in this direction shows the use of Genetic algorithms (GA) as promising candidate and is preferred over other optimization methods. Firstly due to the...

This paper presents a problem-space genetic algorithm (PSGA)-based technique for efficient matching and scheduling of an application program that can be represented by a directed acyclic graph, onto a mixed-machine distributed heterogeneous computing (DHC) system. PSGA is an evolutionary technique that combines the search capability of genetic algorithms with a known fast problem-specific heuri...

In this paper, a new memetic algorithm (MA) for the total tardiness single machine scheduling (SMS) problem with due dates and sequence-dependent setup times is proposed. The main contributions with respect to the implementation of the hybrid population approach are a hierarchically structured population conceived as a ternary tree and the evaluation of three recombination operators. Concerning...

Nowadays, Cloud computing is widely used in companies and enterprises. However, there are some challenges in using Cloud computing. The main challenge is resource management, where Cloud computing provides IT resources (e.g., CPU, Memory, Network, Storage, etc.) based on virtualization concept and pay-as-you-go principle. The management of these resources has been a topic of much research. In t...

The need for calculating actions has been emerged everywhere and in any time, by advancing of information technology. Cloud computing is the latest response to such needs. Prominent popularity has recently been created for Cloud computing systems. Increasing cloud efficiency is an important subject of consideration. Heterogeneity and diversity among different resources and requests of users in ...

this paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. this problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life ti...