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·The concept of parallel machines has been widely used in manufacturing This article proposes a genetic algorithm GA approach to minimize total tardiness of a set of tasks for identical parallel machines and worker assignment to machines A spreadsheet based GA approach is presented to solve the problem A domain independent general
·1 Introduction In manufacturing environments it is ordinary to have different machines operating in parallel each of which with different shifts and inactive time intervals such as for preventive maintenance Li Liu Sethi & Xu 2017 The Unrelated Parallel Machine Scheduling Problem with Machine Availability and Eligibility Constraints
·Scheduling problems are important in many fields including manufacturing logistics and transportation The parallel machine scheduling problem PMSP is a problem with theoretical and practical significance that involves assigning n jobs to m parallel machines for processing Gao et al 2022 In most studies jobs are available at zero
·Qjam is a framework for the rapid prototyping of parallel machine learning algorithms on clusters I Introduction Many machine learning algorithms are easy to parallelize in theory However the xed cost of creating a distributed system that organizes and manages the work is an obstacle to parallelizing existing algorithms and prototyping
·In the past years many researchers has been investigated parallel machine scheduling problem by considering various operational constraints However the first study on parallel machine scheduling problem has been conducted by McNaughton 1959 in the late fifties Other researchers such as Horowitz and Sahni 1976 Cheng and Sin 1990
·We study parallel online algorithms For some fixed integer k a collective of k parallel processes that perform online decisions on the same sequence of events forms a k copy algorithm For any given time and input sequence the overall performance is determined by the best of the k individual total results Problems of this type have been
·5 Uniformly Fine Grained Data Parallel Computing for Machine Learning Algorithms 89 Meichun Hsu Ren Wu and Bin Zhang Overview of a GP GPU 91 Uniformly Fine Grained Data Parallel Computing on a GPU 93 The k Means Clustering Algorithm 97 The k Means Regression Clustering Algorithm 99 Implementations
·This work investigates a stochastic parallel machine scheduling problem where job release times and processing times are uncertain The problem consists of a two stage decision making process i assigning jobs to machines on the first stage before the realisation of uncertain parameters job release times and processing times and ii
·Conventional machine tools are characterized by serial kinematic architectures but parallel mechanisms can provide an inherent increase in kinematic and dynamic performance especially in terms of stiffness speed and repeatability [[3] [4] [5]] Whereas in a serial architecture the tool or end effector if borrowing terminology
·The addressed problem is a multi objective unrelated parallel machine scheduling problem with sequence dependent setup times SDST and machine eligibility constraints In the fabric dyeing industry the fabric to be dyed is first cleaned then dyed then finished with certain chemical treatments as shown in the schematic Fig 1
·Parallel machine models Total Completion Time Parallel machines Pjj P Cj for m = 1 the SPT rule is optimal see Lecture 2 for m 2 a partition of the jobs is needed if a job j is scheduled as k last job on a machine this job contributes kpj to the objective value we have m last positions where the processing time is
·The literature on parallel machine scheduling has developed over multiple decades and contains many useful models and algorithms see for instance [1] [2] [3] One of the most frequently studied objectives in scheduling identical parallel machines is to minimize the makespan the maximum completion time of the jobs
·1 This study considers a two identical parallel machine scheduling problem with machine availability constraints with the objective of minimizing the total completion time It has been assumed in
·In this paper we address the hybrid flow shop scheduling problems with unrelated parallel machines sequence dependent setup times and processor blocking to minimize the makespan and maximum tardiness criteria Since the problem is strongly NP hard we propose an effective algorithm consisting of independent parallel genetic
·In this paper we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant The photolithography workshop is often a bottleneck and improving scheduling decisions in this workshop can help to improve indicators of the whole plant Two optimization criteria
·This paper considers jointly scheduling the production and resource constrained maintenance activities in a manufacturing setting with unrelated parallel machines
·We study parallel machine scheduling for makespan minimization with uncertain job processing times To incorporate uncertainty and generate solutions that are in some way insensitive to unfolding information three different modeling paradigms are adopted a robust model a chance constrained model and a distributionally robust
·A problem of parallel machine scheduling with coordinated job deliveries is handled to minimize the makespan Different jobs call for dissimilar sizes of storing space in the process of transportation tougher to resolve compared with models involving jobs of equal size since the batching decision now involves bin packing which alone is NP
·The unrelated parallel machine scheduling problem with sequence and machine dependent setup times in the presence of due date constraints represents an important but relatively less studied scheduling problem in the literature In this study a simple iterated greedy IG heuristic is presented to minimize the total tardiness of this
·Scheduled Model Parallel Machine Learning Jin Kyu Kim1 Qirong Ho2 Seunghak Lee1 Xun Zheng1 Wei Dai1 Garth A Gibson1 Eric P Xing1 1School of Computer Science As a result all machines sub updates can be easily aggregated This convenient property does not ap ply to model parallel algorithms which introduce new sub
·Language pair Amount of parallel subtitles English German English French English Spanish English Dutch English Swedish English Portuguese Serbian Slovenian Total Table 1 Amount of available parallel subtitles provided by the members of the SUMAT
· ABSTRACT MODELS OF PARALLEL MACHINES The most popular abstraction of a parallel machine is by far the parallel random access machine or PRAM A PRAM consists of a collection of indepen dent processors and a single shared memory It is as sumed that each processor can read or write to any lo cation in the memory in a
·Parallel Machines 1 Parallel Machine Problems 1 Minimising C max For the problem with parallel machines the following two lower bounds of the makespan are often used Job based bound C max ‡ p where p = max{p 1 p 2 p n} 1 makespan cannot be smaller than the time required to complete one job Machine based bound å =
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