Algorithms for large scale Shift Minimisation Personnel Task Scheduling Problems

2012 ◽  
Vol 219 (1) ◽  
pp. 34-48 ◽  
Author(s):  
M. Krishnamoorthy ◽  
A.T. Ernst ◽  
D. Baatar
Keyword(s):  
Task Scheduling ◽  
Large Scale ◽  
Scheduling Problems ◽  
Scale Shift

A large-scale shift of cropland structure profoundly affects grain production in the cold region of China

2021 ◽  
pp. 127300
Author(s):  
Tao Pan ◽  
Chi Zhang ◽  
Wenhui Kuang ◽  
Geping Luo ◽  
Guoming Du ◽  
...  
Keyword(s):  
Large Scale ◽  
Grain Production ◽  
Cold Region ◽  
Scale Shift

scholarly journals Near-Optimal Solutions of Large-Scale Single-Machine Scheduling Problems

2005 ◽  
Vol 17 (2) ◽  
pp. 183-191 ◽  
Author(s):  
Pasquale Avella ◽  
Maurizio Boccia ◽  
Bernardo D’Auria
Keyword(s):  
Single Machine ◽  
Large Scale ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Machine Scheduling Problems

scholarly journals A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6610
Author(s):  
Raka Jovanovic ◽  
Islam Safak Bayram ◽  
Sertac Bayhan ◽  
Stefan Voß
Keyword(s):  
Public Transport ◽  
High Speed ◽  
Large Scale ◽  
Integer Program ◽  
Mixed Integer ◽  
Transport Systems ◽  
Mixed Integer Program ◽  
Scheduling Problems ◽  
Electric Bus ◽  
Battery Capacity

Electrifying public bus transportation is a critical step in reaching net-zero goals. In this paper, the focus is on the problem of optimal scheduling of an electric bus (EB) fleet to cover a public transport timetable. The problem is modelled using a mixed integer program (MIP) in which the charging time of an EB is pertinent to the battery’s state-of-charge level. To be able to solve large problem instances corresponding to real-world applications of the model, a metaheuristic approach is investigated. To be more precise, a greedy randomized adaptive search procedure (GRASP) algorithm is developed and its performance is evaluated against optimal solutions acquired using the MIP. The GRASP algorithm is used for case studies on several public transport systems having various properties and sizes. The analysis focuses on the relation between EB ranges (battery capacity) and required charging rates (in kW) on the size of the fleet needed to cover a public transport timetable. The results of the conducted computational experiments indicate that an increase in infrastructure investment through high speed chargers can significantly decrease the size of the necessary fleets. The results also show that high speed chargers have a more significant impact than an increase in battery sizes of the EBs.

Sign in / Sign up

Export Citation Format

Share Document