Big Data Analytics is an innovative approach for extracting the data from a huge volume of warehouse systems. It reveals method to compress high into clusters by MapReduce and HDFS. However, processing has taken more time extract store in Hadoop clusters. The proposed system deals with challenges delay shuffle phase map-reduce due scheduling sequencing. For improving speed big data, this work u...

Sequencing and scheduling are forms of decision making which play a key role in manufacturing. This paper presents the description of a scheduling algorithm for the solution of the no-wait ̄ow-shop problem. The goal of the heuristic is to minimise the sum of the total ̄owtimes, a criterion which at the same time minimises the average processing time. This is a sensible target in applications su...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

Flexible job shops are characterized by the existence of alternative –not necessarily identicalmachines, which permits parts to have different alternative routes in the shop. In a dynamic scheduling situation in which jobs continuously arrive over time, part routing rules are needed to deal with such routing flexibility as much as sequencing rules which define the order by which parts are admit...

The optimal scheduling of crude-oil operation in refineries has been studied by various groups during the past decade, leading to different mixed integer linear programming or mixed nonlinear programming formulations. This paper proposes a new MINLP formulation with an oil residency time constraint and common pipeline transportation that is based on single-operation sequencing (SOS). An effecti...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

We revisit the classical stochastic scheduling problem of nonpreemptively scheduling n jobs so as to minimize total completion time on m identical machines, P || E ∑ Cj in the standard 3field scheduling notation. Previously it was only known how to obtain reasonable approximation if jobs sizes have low variability. However, distributions commonly arising in practice have high variability, and t...

In interval scheduling, not only the processing times of the jobs but also their starting times are given. This paper surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability of different variants of interval scheduling problems. Next, we motivate the relevance of interval s...

Abstract This article analyzes the content related to big data and artificial intelligence technology. The author studied characteristics of COVID-19 epidemic, epidemic characteristics, transmission routes. has use technologies in genome sequencing analysis, intelligent medical diagnostic services, vaccine research development drug screening, reasonable scheduling anti-epidemic resources, monit...

this paper presents a simplifiedlagrangian multiplier based algorithm to solve the fixed head hydrothermalscheduling problem. in fixed head hydrothermal scheduling problem, waterdischarge rate is modeled as quadratic function of hydropower generation andfuel cost is modeled as quadratic function of thermal power generation. thepower output of each hydro unit varies with the rate of water discha...