Stability and fairness in the job scheduling problem

Bahel, Eric; Trudeau, Christian

doi:10.1016/j.geb.2019.06.006

Cited by 13 publications

(8 citation statements)

References 23 publications

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“…For low-earth-orbit (LEO) satellites, the requested communication time may last for the entire time window due to the short time window duration. If the entire time window is utilized for communication, scheduling LEO satellite requests is similar to the job scheduling problem [40]. For high-earth-orbit (HEO) satellites, the available time window in longer than the requested duration, which means both the time window and the exact execution time should be determined.…”

Section: Problem Formulation a Preliminariesmentioning

confidence: 99%

Evolutionary Multiobjective Satellite Range Scheduling With Learning-Guided Population Generation

Xiong

Zheng

2022

IEEE Access

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Most existing evolutionary approaches to satellite range scheduling seek optimal solution in terms of the request satisfaction. The scheduling demand of managing ground station resource is seldom considered, which restricts their real-world applications. To effectively generate a set of more rational satellite range schedules, this paper establishes the multi-objective satellite range scheduling mathematical model. Unlike existing approaches, we propose a general population generation approach to solve the problem without relying on any specific kind of evolutionary algorithm, so different types of evolutionary algorithms can be extended to satellite range scheduling without modifying the original framework and search strategy. The idea is to utilize the request satisfaction and resource utilization knowledge learnt from parent schedules to guide the generation and updating of new solutions. Furthermore, an iterative rewriting operator is designed to guide a biased faster convergence towards the low request failure region in objective space. The proposed approach has been applied to five different types of classical and state-ofthe-art evolutionary algorithms and examined on benchmark problems. Experimental results illustrate the search efficiency enhancement and good adaptability to different evolutionary algorithms, which show the broad application prospect for satellite range scheduling.

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Section: Problem Formulation a Preliminariesmentioning

confidence: 99%

Evolutionary Multiobjective Satellite Range Scheduling With Learning-Guided Population Generation

Xiong

Zheng

2022

IEEE Access

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“…Then, Core(C M ) is non-empty. A particular subset of minimum coloring problems is the set of job scheduling problems (Bahel and Trudeau (2019)). In those problems, each agent has a single job that has a starting and finishing time, and must be processed on a machine without interruption from the starting to the finishing time.…”

Section: Compatibility Problemsmentioning

confidence: 99%

“…A sufficient condition for the non-vacuity of the core is provided, requiring that for any subset of agents, the number of groups needed to avoid conflicts (the chromatic number of the graph) is equal to the size of the largest group of agents all in conflict with each other (the size of the largest clique in the graph). A simpler version where the condition is always verified is presented by Bahel and Trudeau (2019) where agents have time-sensitive jobs to be processed on a machine, and in which we are trying to determine the smallest number of machines required to process all jobs without conflict. We show that when the condition of Okamoto (2008) is verified, we have representability as a MSP problem.…”

Section: Introductionmentioning

confidence: 99%

Stable Source Connection and Assignment Problems as Multi-Period Shortest Path Problems

Streekstra

Trudeau

2020

SSRN Journal

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We extend the familiar shortest path problem by supposing that agents have demands over multiple periods. This potentially allows agents to combine their paths if their demands are complementary; for instance if one agent only needs a connection to the source in the summer while the other requires it only in the winter.We show that the resulting cost sharing problem always has a non-empty core, regardless of the number of agents and periods, the cost structure or the demand profile.We then exploit the fact that the model encompasses many well-studied problems to obtain or reobtain non-vacuity results for the cores of source-connection problems, (m-sided) assignment problems and minimum coloring problems.

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“…In short, a machine, which serves one job at a time, is shared by users with jobs of arbitrary length and waiting-time costs, and the question is how users share the joint externality by suitable side payments. Recently, Bahel and Trudeau (2019) consider a version of classic job scheduling with a focus on fair division of the efficient cost using the framework of cooperative game theory. They provide a characterization of stable cost allocations in the sense of the core as well as axiomatic characterizations of two allocation rules.…”

Section: Introductionmentioning

confidence: 99%