• Title/Summary/Keyword: completion time algorithm

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Scate: A Scalable Time and Energy Aware Actor Task Allocation Algorithm in Wireless Sensor and Actor Networks

  • Sharifi, Mohsen;Okhovvat, Morteza
    • ETRI Journal
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    • v.34 no.3
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    • pp.330-340
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    • 2012
  • In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules, and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms, namely, the max-min, min-min, and opportunistic load balancing algorithms, is used.

Solution of the Resource Constrained Project Scheduling Problem on the Foundation of a Term-Based Approach (Term-Based Approach를 기초로한 자원제한프로젝트스케줄링 문제의 해결)

  • Kim, Pok-Son
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.2
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    • pp.218-224
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    • 2014
  • The logic-based scheduling language RCPSV may be used to model resource-constrained project scheduling problems with variants for minimizing the project completion time. A diagram-based, nonredundant enumeration algorithm for the RCPSV-problem is proposed and the correctness of the algorithm is proved.

A heuristic algorithm for resource constrained scheduling with flexible resource allocation (유연자원할당 및 자원제약하의 일정계획을 위한 발견적 알고리즘)

  • Yoo, Jae-Gun
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.2
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    • pp.433-450
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    • 1997
  • In this study, a heuristic algorithm is developed to solve a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories, and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The algorithm takes advantage of the basic structure of a heuristic algorithm, called the exchange heuristic, but employs different strategies on some critical steps of the original algorithm which have significant effects on the algorithm performance. The original algorithm and the modified algorithm were compared through an experimental investigation. The modified algorithm produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time.

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A Heuristic Algorithm for Resource-Constrained Multi - Project Scheduling (자원제약하의 복수 프로젝트 일정계획을 위한 휴리스틱 알고리즘)

  • Kong, Myung-Dal;Kim, Jung-Ja
    • IE interfaces
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    • v.13 no.1
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    • pp.110-119
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    • 2000
  • Resource-constrained project scheduling is to allocate limited resources to activities to optimize certain objective functions and to determine a start time for each activity in the project such that precedence constraints and resource requirements are satisfied. This study suggests a multi-project scheduling model which can level work loads, make the most of production capacity and restrain the delay of delivery by developing a heuristic algorithm which minimizes the project completion time and maximizes the load rate under resource constraints.

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LPT Scheduling for Multipurpose Machines (여러 종류의 작업 처리가 가능한 기계 시스템에 대한 LPT 스케줄링)

  • Hwang, Hark-Chin
    • IE interfaces
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    • v.16 no.spc
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    • pp.132-137
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    • 2003
  • We consider scheduling jobs on multipurpose machines where jobs can be processed by a subset of the machines operated in parallel with the objective of minimizing makespan. We apply LPT(Longest Processing Time first) algorithm and prove that its posterior worst-case performance ratio is at most $log_24m/(1+{\lambda})$, where \lambda is the number of machines eligible for processing the job with the latest completion time. In general, LPT is shown to always find a schedule with makespan at most $log_24m/3$ times optimum.

Optimal Project Duration Estimation Through Enhanced Resource Leveling Technique (개선된 자원 평준화 기법을 활용한 적정 공기산정에 관한 연구)

  • Yoon Yung-Sang;Kim Kyung-Hwan;Kim Jae-Jun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2004.11a
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    • pp.575-578
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    • 2004
  • Since a construction project is a series of works that utilizes resources to accomplish the project goal for a given time period, efficient resource management is a prerequisite for the success of the project. Two major areas of resource management are resource constrained scheduling focusing on the limited resource availability and resource leveling focusing on smoothing resource usage pattern on the fixed project completion time. It is not available, however, to apply both techniques to a project at the same time. This paper proposes a model to enhance the minimum moment algorithm of resource leveling, aiming to find an efficient usage of resources and an appropriate project completion time. A survey is performed to evaluate the major five factors using the AHP.

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A Genetic Algorithm for Minimizing Completion Time with Non-identical Parallel Machines (이종 병렬설비 공정의 작업완료시간 최소화를 위한 유전 알고리즘)

  • Choi, Yu Jun;Song, Han Sik;Lee, Ik Sun
    • 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.

A Study on Memetic Algorithm-Based Scheduling for Minimizing Makespan in Unrelated Parallel Machines without Setup Time (작업준비시간이 없는 이종 병렬설비에서 총 소요 시간 최소화를 위한 미미틱 알고리즘 기반 일정계획에 관한 연구)

  • Tehie Lee;Woo-Sik Yoo
    • Journal of the Korea Safety Management & Science
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    • v.25 no.2
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    • pp.1-8
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    • 2023
  • This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

Minimizing the total completion time in a two-stage flexible flow shop (2 단계 유연 흐름 생산에서 평균 완료 시간 최소화 문제)

  • Yoon, Suk-Hun
    • Journal of Convergence for Information Technology
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    • v.11 no.8
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    • pp.207-211
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    • 2021
  • This paper addresses a two-stage flexible flow shop scheduling problem in which there is one machine in stage 1 and two identical machines in stage 2. The objective is the minimization of the total completion time. The problem is formulated by a mixed integer quadratic programming (MIQP) and a hybrid simulated annealing (HSA) is proposed to solve the MIQP. The HSA adopts the exploration capabilities of a genetic algorithm and incorporates a simulated annealing to reduce the premature convergence. Extensive computational tests on randomly generated problems are carried out to evaluate the performance of the HSA.

Batch Scheduling Algorithm with Approximation of Job Completion Times and Case Studies (작업완료시각 추정을 활용한 배치 스케줄링 및 사례 연구)

  • Kim, Song-Eun;Park, Seong-Hyeon;Kim, Su-Min;Park, Kyungsu;Hwang, Min Hyung;Seong, Jongeun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.4
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    • pp.23-32
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    • 2020
  • Many small and medium-sized manufacturing companies process various product types to respond different customer orders in a single production line. To improve their productivity, they often apply batch processing while considering various product types, constraints on batch sizes and setups, and due date of each order. This study introduces a batch scheduling heuristic for a production line with multiple product types and different due dates of each order. As the process times vary due to the different batch sizes and product types, a recursive equation is developed based on a flow line model to obtain the upper bound on the completion times with less computational complexity than full computation. The batch scheduling algorithm combines and schedules the orders with same product types into a batch to improve productivity, but within the constraints to match the due dates of the orders. The algorithm incorporates simple and intuitive principles for the purpose of being applied to small and medium companies. To test the algorithm, two case studies are introduced; a high pressure coolant (HPC) manufacturing line and a press process at a plate-type heat exchanger manufacturer. From the case studies, the developed algorithm provides significant improvements in setup frequency and thus convenience of workers and productivity, without violating due dates of each order.