K. S. Lui and S. Zaks. Scheduling in synchronous networks and the greedy algorithm. In Proceedings of the 11th International Workshop on Distributed Algorithms (WDAG 97), Sept. 1997.Scheduling in synchronous networks and the greedy algorithm - Lui, Zaks () Citation Context ... It is said ...
The simulation results demonstrated that one of the proposed algorithms outperformed all the other compared ones. Arroyo and Leung [26] studied the scheduling of the jobs with different sizes and ready times on unrelated parallel BPMs, and proposed an iterated greedy (IG) algorithm to minimize the...
Although there are some algorithms have been proposed to handle the problem of task scheduling, existing methods mainly focus on reducing the task execution time while ignoring the other factors such as workload balance and QoS. In this paper, we put forward a novel algorithm named ITSA (...
Greedy algorithm for automatic scheduling scheduleschedulerschedulinggreedyscheduling-algorithmsscheduling-problemscheduling-api UpdatedOct 2, 2023 Python Constraint-based timetable generator for students of the Faculty of Organization and Informatics (University of Zagreb) ...
展开 关键词: Theoretical or Mathematical/ flow shop scheduling greedy algorithms/ greedy algorithm permutation flowshop scheduling metaheuristic NEH construction heuristic/ C1290F Systems theory applications in industry E1010 Production management E1540 Systems theory applications DOI...
This paper describes the core algorithm used in an implementation of a scheduler currently being installed in a major Asian railway. It extends previous work on a greedy heuristic for scheduling trains, to provide a powerful and practically useful method that is fast enough for real-time use in...
In this paper, we remove the static capacity constraint, and doing so allows a vehicle to carry more passengers than its capacity. We propose a greedy approach based on iterative matching and merging. Specifically, starting from a set of single-user carpools, the algorithm iteratively checks ...
The energy consumption models in relevant studies were compared and classified. A thorough comparative analysis of energy-efficient DRL-based task scheduling was conducted, considering various aspects such as RL/DRL algorithms, task types, scheduling objectives, state spaces, action spaces, reward ...
This paper presents scheduling algorithms for procrastinators, where the speed that a procrastinator executes a job increases as the due date approaches. We give optimal off-line scheduling policies for linearly increasing speed functions. We then explain the computational/numerical issues involved in imp...
In some complex scenarios with difficulties in directly evaluating the performance of scheduling solutions, classic algorithms (such as heuristics and meta-heuristics) will fail to obtain an effective scheme. Deep reinforcement learning (DRL) is a novel method to solve scheduling problems. Due to the...