• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1B
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• pp.27-32
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• 2003

This paper presents the Genetic Algorithm based Task Scheduling (GATS) method for the scheduling of programs with diverse embedded parallelism types in Distributed Parallel Systems, which consist of a set of loosely coupled parallel and vector machines connected via high speed networks The distributed parallel processing tries to solve computationally intensive problems that have several types of parallelism, on a suite of high performance and parallel machines in a manner that best utilizes the capabilities of each machine. When scheduling in distributed parallel systems, the matching of the parallelism characteristics between tasks and parallel machines rather than load balancing should be carefully handled with the minimization of communication cost in order to obtain more speedup. This paper proposes the based initialization methods for an initial population and the knowledge-based mutation methods to accommodate the parallelism type matching in genetic algorithms.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.15-23
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• 2011

This research considers scheduling problems with jobs which can be divided into sub-jobs and do not required to be processed immediately following one another. Heuristic algorithms considering how to divide jobs are proposed in an attempt to find near-optimal solutions within reasonable run time. The algorithms contain two phases which are executed recursively. Phase 1 of the algorithm determines how jobs should be divided while phase 2 solves the scheduling problem given the sub-jobs established in phase 1. Simulated annealing and genetic algorithms are applied for the two phases and four heuristic algorithms are established. Numerical experiment is conducted to determine the best parameter values for the heuristic algorithms. Examples with different sizes and levels of complexity are generated. Performance of the proposed algorithms is evaluated. It is shown that the proposed algorithms are able to efficiently and effectively solve the considered problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.65-73
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• 2015

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines using GA (Genetic Algorithm). Non-identical setup times, processing times and order lot size are assumed for each machine. The GA is proposed to minimize the total-tardiness objective measure. In this paper, heuristic algorithms including EDD (Earliest Due-Date), SPT (Shortest Processing Time) and LPT (Longest Processing Time) are compared with GA. The effectiveness and suitability of the GA are derived and tested through computational experiments.

• Korean Management Science Review
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• v.30 no.3
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• pp.81-97
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• 2013

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines. Non-identical setup and processing times are assumed for each machine. A genetic algorithm is proposed to minimize the makespan objective measure. In this paper, a lowerbound and some heuristic algorithms are derived and tested through computational experiments.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.289-293
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• 2000

We propose two new algorithms for parallelism-independent scheduling. The machine code generated from the compiler using these algorithms in its scheduling phase is parallelism-independent code, executable in minimum time regardless of the number of the processors in the parallel computer. Our new algorithms have the following phases: finding the minimum number of processors on which the program can be executed in minimal time, scheduling by an heuristic algorithm for this predefined number of processors, and serialization of the parallel schedule according to the earliest start time of the tasks. At run time tasks are taken from the serialized schedule and assigned to the processor which allows the earliest start time of the task. The order of the tasks decided at compile time is not changed at run time regardless of the number of the available processors which means there is no out-of-order issue and execution. The scheduling is done predominantly at compile time and dynamic scheduling is minimized and diminished to allocation of the tasks to the processors. We evaluate the proposed algorithms by comparing them in terms of schedule length to the CP/MISF algorithm. For performance evaluation we use both randomly generated DAGs (directed acyclic graphs) and DACs representing real applications. From practical point of view, the algorithms we propose can be successfully used for scheduling programs for in-order superscalar processors and shared memory multiprocessor systems. Superscalar processors with any number of functional units can execute the parallelism-independent code in minimum time without necessity for dynamic scheduling and out-of-order issue hardware. This means that the use of our algorithms will lead to reducing the complexity of the hardware of the processors and the run-time overhead related to the dynamic scheduling.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.35-46
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• 1987

To minimize makespan for preemptive sequence dependent job scheduling with parallel identical processors, fundamental results, as the basis of new algorithm to be presented, such as McNauton's algorithm for independent jobs, Hu's characterization for dependent jobs, and Muntz-Coffman's algorithm, were first introduced. Then a huristic procedure was presented applying those concepts of zoning of assembly line balancing and of resource leveling on CPM network scheduling with two or more of parallel machines in general. New procedure has eliminated presumative machine assignment using ${\rho}$, rate of resource capability (${\rho}$ < 1), for practical scheduling.

• IE interfaces
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• v.15 no.4
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• pp.338-348
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• 2002

In this paper, we present a restricted tabu search(RTS) algorithm that schedules jobs on identical parallel machines in order to minimize the maximum lateness of jobs. Jobs have release times and due dates. Also, sequence-dependent setup times exist between jobs. The RTS algorithm consists of two main parts. The first part is the MATCS(Modified Apparent Tardiness Cost with Setups) rule that provides an efficient initial schedule for the RTS. The second part is a search heuristic that employs a restricted neighborhood generation scheme with the elimination of non-efficient job moves in finding the best neighborhood schedule. The search heuristic reduces the tabu search effort greatly while obtaining the final schedules of good quality. The experimental results show that the proposed algorithm gives better solutions quickly than the existing heuristic algorithms such as the RHP(Rolling Horizon Procedure) heuristic, the basic tabu search, and simulated annealing.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.202-211
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• 2023

The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.35-35
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• 1993

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.102-102
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• 1992