A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

Yu, Fei; Wen, Peihan; Yi, Shu Ping

doi:10.1177/1687814018756103

Cited by 19 publications

(13 citation statements)

References 24 publications

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“…e literature studies other variants of the two-agent scheduling problem. However, they differ from the problem considered in this paper in terms of either objective function (Wan et al [21]; Mor and Mosheiov [22]) or machine settings (Mor and Mosheiov [23]; Lei [24]; Yu et al [25]). A literature survey by Li et al [26] and Yin et al [27] can be referred to find different variants of the two-agent scheduling problem with due date-related objectives.…”

Section: Two-agent Scheduling Problem With the Number Of Tardymentioning

confidence: 78%

Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time

Gajpal

Surti

et al. 2020

Complexity

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This paper delves into a two-agent scheduling problem in which two agents are competing for a single resource. Each agent has a set of jobs to be processed by a single machine. The processing time, release time, weight, and the due dates of each job are known in advance. Both agents have their objectives, which are conflicting in nature. The first agent tries to minimize the total completion time, while the second agent tries to minimize the number of tardy jobs. The two agents’ scheduling problem, an NP-hard problem, has a wide variety of applications ranging from the manufacturing industry to the cloud computing service provider. Due to the wide applicability, each variation of the problem requires a different algorithm, adapted according to the user’s requirements. This paper provides mathematical models, heuristic algorithms, and two nature-based metaheuristic algorithms to solve the problem. The algorithm’s performance was gauged against the optimal solution obtained from the AMPL-CPLEX solver for both solution quality and computational time. The outlined metaheuristics produce a solution that is comparable with a short computational time. The proposed metaheuristics even have a better solution than the CPLEX solver for medium-size problems, whereas the computation times are much less than the CPLEX solvers.

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Section: Two-agent Scheduling Problem With the Number Of Tardymentioning

confidence: 78%

Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time

Gajpal

Surti

et al. 2020

Complexity

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“…Some relevant literatures suggested that the LPT algorithm on addressing makespan minimization problem is quite appropriate. 5,29,30,[31][32][33][34][35] LPT algorithm: Sort all jobs in non-increasing order of their processing times. Each job is subsequently assigned to a machine on which it can be finished as early as possible.…”

Section: Worst-case Ratio Analysismentioning

confidence: 99%

A parallel-machine scheduling with periodic constraints under uncertainty

Shen

Zhu

2019

Advances in Mechanical Engineering

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Most studies on scheduling problem have assumed that the machine is continuously available. However, the machine is likely to be unavailable for many practical reasons (e.g. breakdown and planned preventive maintenance). Once a machine is not available, the optimal scheme in the deterministic scenario may not be the optimal choice. To address the actual scenario, a scheduling problem with two identical parallel machines, one of which requires periodic maintenance, is considered in this article. For uncertainties in reality, the processing and maintenance time are considered as uncertain variables. A novel method to study the worst-case ratio in an uncertain scenario is proposed. It is shown that the worst-case ratio of the longest processing time algorithm is 3/2 at a high confidence level. Given theoretical analysis results, an modified algorithm is proposed. Finally, numerical experiments are used to verify the feasibility of the modified algorithm.

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“…Consequently, schedules that minimize the total tardiness lead to high performance, customer satisfaction, and minimum penalty. For more recent development in minimizing total tardiness, readers can refer to [2][3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Minimizing the Total Tardiness of a Game Project Considering the Overlap Effect

2020

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There has long been a custom that game development is not the mainstream of engineering and its tardiness brings little or even no harm to this industry. Nowadays, the pendulum of industrial development has swung to another side. A game project may involve hundreds of developers, thousands of jobs, and millions of costs. Situations would be worse if jobs overlap with others. Any delay of a large game project can cause a heavy penalty. Consequently, in this study, we propose two scheduling algorithms to reduce the total tardiness of a game project. If the problem size is small, a branch-and-bound algorithm is employed to provide the optimal schedules; otherwise a genetic algorithm is used to generate near-optimal schedules. The experimental results show that the proposed algorithms reduce the total tardiness significantly.

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A multi-agent scheduling problem for two identical parallel machines to minimize total tardiness time and makespan

Cited by 19 publications

References 24 publications

Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time

Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time

A parallel-machine scheduling with periodic constraints under uncertainty

Minimizing the Total Tardiness of a Game Project Considering the Overlap Effect

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