Simultaneous Scheduling of Machines and Tools in a Multi Machine FMS with Alternate Machines Using Crow Search Algorithm

2021 ◽  
Author(s):  
N. Sivarami Reddy ◽  
M. Padma Lalitha ◽  
D. V. Ramamurthy ◽  
K. Prahlada Rao
Keyword(s):  
Search Algorithm ◽  
Simultaneous Scheduling

Scheduling of Machines and Automated Guided Vehicles in FMS Using Gravitational Search Algorithm

2017 ◽  
Vol 867 ◽  
pp. 307-313 ◽  
Author(s):  
Medikondu Nageswararao ◽  
K. Narayanarao ◽  
G. Rangajanardhana
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Automated Guided Vehicles ◽  
Gravitational Search ◽  
Simultaneous Scheduling

A new meta-heuristic gravitational search(GS) algorithm is proposed for simultaneous scheduling of machines, and two identical automated guided vehicles(AGVs) in a flexible manufacturing system(FMS). It minimize the makespan and completes the assigned jobs faster with possible savings of the resources. The adequacy of the algorithm is demonstrated by solving several problems and comparing with existing results.

scholarly journals Simultaneous scheduling of machines and tools in a multi machine FMS with alternative routing using symbiotic organisms search algorithm

2021 ◽  
Author(s):  
Dr.N.Sivarami Reddy ◽  
◽  
Dr. M.Padma Lalitha ◽  
Dr. S.P. Pandey ◽  
Dr. G.S. Venkatesh ◽  
...  
Keyword(s):  
Flexible Manufacturing ◽  
Search Algorithm ◽  
Mixed Integer ◽  
Symbiotic Interaction ◽  
Symbiotic Organisms Search ◽  
Tool Magazine ◽  
Operations Sequencing ◽  
Alternative Routing ◽  
Symbiotic Organisms ◽  
Simultaneous Scheduling

This paper deals with simultaneous scheduling of machines and tools with alternate machines in a multi machine flexible manufacturing system (FMS) to minimize makespan (MS). Only one copy of each type of tools is made available due to economic restrictions and the tools are stored in a central tool magazine (CTM) that shares with and serves for several machines. The problem is to select machines from alternate machines for job-operations, allocation of tools to job-operations and job-operations’ sequencing on machines for MS minimization. This paper presents a nonlinear mixed integer programming (MIP) formulation to model the combined scheduling of machines and tools with alternate machines and a symbiotic organisms search algorithm (SOSA) built on the symbiotic interaction strategies that organisms employ to continue to exist in the ecosystem for solving the scheduling of machines and tools with alternate machines. The results have been tabulated, analyzed. It is observed that there is a reduction in MS when the alternate machines are considered for job-operation.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

An Improved Version of Algebraic Codebook Search Algorithm for an AMR-WB Speech Coder

Informatica ◽  
2017 ◽  
Vol 28 (2) ◽  
pp. 403-414 ◽  
Author(s):  
Ming-Che Yeh ◽  
Cheng-Yu Yeh ◽  
Shaw-Hwa Hwang
Keyword(s):  
Search Algorithm ◽  
Speech Coder
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