scholarly journals Heuristic approach for the multiobjective optimization of the customized bus scheduling problem

2021 ◽  
Author(s):  
Kaijun Liu ◽  
Jianming Liu ◽  
Jingwei Zhang
Keyword(s):  
Multiobjective Optimization ◽  
Heuristic Approach ◽  
Scheduling Problem ◽  
Bus Scheduling

A school bus scheduling problem

2012 ◽  
Vol 218 (2) ◽  
pp. 577-585 ◽  
Author(s):  
Byung-In Kim ◽  
Seongbae Kim ◽  
Junhyuk Park
Keyword(s):  
Scheduling Problem ◽  
School Bus ◽  
Bus Scheduling

scholarly journals A Two-Stage Offline-to-Online Multiobjective Optimization Strategy for Ship Integrated Energy System Economical/ Environmental Scheduling Problem

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qing An ◽  
Jun Zhang ◽  
Xin Li ◽  
Xiaobing Mao ◽  
Yulong Feng ◽  
...  
Keyword(s):  
Multiobjective Optimization ◽  
Real World ◽  
Operation Time ◽  
Energy System ◽  
Scheduling Problem ◽  
Storage Space ◽  
Optimization Strategy ◽  
Two Stage ◽  
Integrated Energy System ◽  
And Storage

The economical/environmental scheduling problem (EESP) of the ship integrated energy system (SIES) has high computational complexity, which includes more than one optimization objective, various types of constraints, and frequently fluctuated load demand. Therefore, the intelligent scheduling strategies cannot be applied to the ship energy management system (SEMS) online, which has limited computing power and storage space. Aiming at realizing green computing on SEMS, in this paper a typical SIES-EESP optimization model is built, considering the form of decision vectors, the economical/environmental optimization objectives, and various types of real-world constraints of the SIES. Based on the complexity of SIES-EESPs, a two-stage offline-to-online multiobjective optimization strategy for SIES-EESP is proposed, which transfers part of the energy dispatch online computing task to the offline high-performance computer systems. The specific constraints handling methods are designed to reduce both continuous and discrete constraints violations of SIES-EESPs. Then, an establishment method of energy scheduling scheme-base is proposed. By using the big data offline, the economical/environmental scheduling solutions of a typical year can be obtained and stored with more computing resources and operation time on land. Thereafter, a short-term multiobjective offline-to-online optimization approach by SEMS is considered, with the application of multiobjective evolutionary algorithm (MOEA) and typical schemes corresponding to the actual SIES-EESPs. Simulation results show that the proposed strategy can obtain enough feasible Pareto solutions in a shorter time and get well-distributed Pareto sets with better convergence performance, which can well adapt to the features of real-world SIES-EESPs and save plenty of operation time and storage space for the SEMS.

The airport shuttle bus scheduling problem

2020 ◽  
pp. 1-23
Author(s):  
Nihat Öner ◽  
Hakan Gultekin ◽  
Çağrı Koç
Keyword(s):  
Scheduling Problem ◽  
Bus Scheduling
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