scholarly journals Optimization of Material Transportation Assignment for Automated Guided Vehicle (AGV) System

2018 ◽  
Vol 7 (3.20) ◽  
pp. 334 ◽  
Author(s):  
Nor Rashidah Mohamad ◽  
Muhammad Hafidz Fazli Md Fauadi ◽  
Siti Fairus Zainudin ◽  
Ahamad Zaki Mohamed Mohamed Noor ◽  
Fairul Azni Jafar ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Performance Enhancement ◽  
Optimal Solution ◽  
Task Assignment ◽  
Automated Guided Vehicles ◽  
Assignment Method ◽  
Material Transportation ◽  
And Performance ◽  
Optimization And Performance

This article focuses on Material Transportation Assignment problem that is identified as an Automated Guided Vehicles (AGV) multi-load task assignment. The primary goal of this paper is to determine the factors needed to optimize material transportation system. This study also explores the optimization and performance enhancement of the Flexible Manufacturing System (FMS) environment. The implementation of Genetic Algorithm (GA) in this model is to obtain the optimal solution for FMS layout. The combination of delivery and pickup task are addressed by modified algorithm for advancement in multiple loads AGV. The result obtained depicts that the proposed task assignment method with a modified genetic algorithm can produce acceptable performance compared to conventional task assignment method.  

A Petri Net and Genetic Algorithm Based Method for Flexible Manufacturing Cells Modeling and Scheduling

2009 ◽  
Vol 407-408 ◽  
pp. 268-272 ◽  
Author(s):  
Li Hong Qiao ◽  
Yi Xin Zhu ◽  
Jian Jun Yang ◽  
Yang Li
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Petri Net ◽  
Flexible Manufacturing ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Manufacturing Cells ◽  
Flexible Manufacturing Cells ◽  
Annealing Algorithm

The production organized in flexible manufacturing cells (FMC) can be a complicated issue when they are constrained by machines, robots, equipment and some other resources. Since machines and robots are the main bottleneck to the efficiency of FMC, this paper focused on the modeling and scheduling problem constrained by machines and robots. A common model representation, colored timed Petri net (CTPN) was utilized to build a FMC model constrained by robots and machines, which was then transformed to the simulation model. The scheduling problem was studied to establish a mathematical model of the FMC constrained by machines and robots. According to the model, a genetic algorithm was proposed to search an optimal solution by using an indirect coding of scheme. The effectiveness of the proposed algorithm was validated via an instance and the comparison with the result from the solution of simulated annealing algorithm.

Reactive Scheduling of a Decentralized Multi-Objective Material Transportation Tasks in a Dynamic Job Shop Manufacturing System

2014 ◽  
Vol 564 ◽  
pp. 597-603
Author(s):  
Muhammad Hafidz Fazli bin Md Fauadi ◽  
Fairul Azni Jafar ◽  
Adi Saptari ◽  
Wan Ling Li
Keyword(s):  
Manufacturing Industry ◽  
Manufacturing System ◽  
Job Shop ◽  
Task Assignment ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Dynamic Factors ◽  
Multi Agent ◽  
Material Transportation ◽  
Dynamic Job Shop

The increasingly challenging and dynamic nature of manufacturing industry has driven organizations to enhance their system efficiency. One of the most important aspects in manufacturing plant is the Material Transportation System (MTS). In order to address dynamic factors, MTS need to be equipped with rescheduling capability. This paper focuses on reactive transportation task assignment to a fleet of autonomous Automated Guided Vehicles (AGVs). This paper proposes a Mixed Integer Programming method to reschedule transportation tasks for a non-disruptive job shop manufacturing system based on Multi Agent System (MAS) architecture. The result shows that proposed rescheduling method is able to outperform conventional method significantly.

Application of Real-Coded Genetic Algorithm in Ship Weather Routing

2018 ◽  
Vol 71 (4) ◽  
pp. 989-1010 ◽  
Author(s):  
Hong-Bo Wang ◽  
Xiao-Gang Li ◽  
Peng-Fei Li ◽  
Evgeny I. Veremey ◽  
Margarita V. Sotnikova
Keyword(s):  
Genetic Algorithm ◽  
Convergence Rates ◽  
Dynamic Environment ◽  
Route Planning ◽  
Optimal Solution ◽  
Population Diversity ◽  
Assignment Method ◽  
Weather Routing ◽  
Fitness Value ◽  
Real Coded Genetic Algorithm

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

scholarly journals SEGMENT RANDOM INSERTION PERTURBATION SCHEME (SRIPS) GENETIC ALGORITHM FOR MANUFACTURING INDUSTRY

2021 ◽  
Vol 9 (2) ◽  
pp. 77-91
Author(s):  
Dr. Nageswara Rao.M, Et. al.
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing Industry ◽  
Automated Guided Vehicles ◽  
Mixed Integer ◽  
Perturbation Scheme ◽  
Mip Model ◽  
Formal Framework ◽  
Simultaneous Scheduling ◽  
Random Insertion

This paper lays down a formal framework for simultaneous scheduling of machines- automated guided vehicles (AGVs) and tools in a multi-machine flexible manufacturing system (FMS) while accounting for transport times of parts to minimise makespan. To minimize tooling costs- a central tool magazine (CTM) is suggested so that the tools are ‘shared’. AGVs and tool transporter (TT) carry jobs and tools between machines. The complexity of including sequencing of job operations on machines- assignment of AGVs and tools to job operations and corresponding trip operations such as the empty trip and loaded trip times of AGVs and a CTM in scheduling is greater. The scope of this paper is to propose a nonlinear Mixed Integer Programming (MIP) model to minimize makespan. Since the problem is known to be NP hard- it is conjectured and then verified that the intelligent behaviour of chromosomes and genes can be effectively used to lay down a metaheuristic algorithm known as a segment random insertion perturbation scheme genetic algorithm (SRIPSGA) suitable for the problem at hand- and the results have been tabulated and analyzed.

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