Energy-Efficient Task Scheduling Algorithms with Human Intelligence Based Task Shuffling and Task Relocation

2011 ◽  
Author(s):  
Zhibo Wang ◽  
Yan-Qing Zhang
Keyword(s):  
Task Scheduling ◽  
Energy Efficient ◽  
Scheduling Algorithms ◽  
Human Intelligence ◽  
And Task

scholarly journals Energy efficient routing and task scheduling for autonomous transfer vehicles in intra logistics

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
Inci Saricicek ◽  
◽  
Sinem Bozkurt Keser ◽  
Azmi Cibi ◽  
Tahir Ozdemir ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Energy Efficient ◽  
Simulated Annealing Algorithm ◽  
Test Problems ◽  
Energy Efficient Routing ◽  
Logistics Industry ◽  
Routing And Scheduling ◽  
Trade Offs ◽  
Hybrid Simulated Annealing ◽  
And Task

Autonomous Transfer Vehicles (ATVs) are becoming increasingly prevalent in intra logistics. Industry 4.0 is bringing us closer to the efficient routing and scheduling of autonomous multi robot systems which perform transportation tasks. In this study, an energy efficient routing and scheduling system is proposed to minimize the total energy that the vehicles spend. Not only travelled distance but also the load of the vehicle is considered between two points. The routes of vehicles are obtained by using the proposed Hybrid Simulated Annealing Algorithm. An algorithm for the initial solution is also proposed for determining of the minimum number of vehicles for pickup and delivery requests. The performance of the algorithm is compared with the best solutions of the test problems in the literature. Besides, the proposed energy efficient routing and task scheduling model is compared with the classical distance model for routing and scheduling with backhauls. An analysis of trade-offs between energy and distance is proposed for intra logistics.

scholarly journals Energy Efficient Motion Design and Task Scheduling for an Autonomous Vehicle

2019 ◽  
Vol 1 (1) ◽  
pp. 2853-2862
Author(s):  
Elias Xidias ◽  
Philip Azariadis
Keyword(s):  
Task Scheduling ◽  
Energy Efficient ◽  
Autonomous Vehicle ◽  
Industrial Sector ◽  
Pareto Optimum ◽  
Optimization Strategy ◽  
Modified Genetic Algorithm ◽  
Pareto Optimum Solution ◽  
Optimum Solution ◽  
And Task

AbstractThis paper describes an approach for designing an energy efficient motion and task scheduling for an autonomous vehicle which is moving in complicated environments in industrial sector or in large warehouses. The vehicle is requested to serve a number of workstations while moving safely and efficiently in the environment. In the proposed approach, the overall problem is formulated as a constraint optimization problem by using the Bump-Surface concept. Then, a Pareto-based multi- objective optimization strategy is adopted, and a modified genetic algorithm is developed to determine the Pareto optimum solution. The efficiency of the developed method is investigated and discussed through simulated experiments.

Sign in / Sign up

Export Citation Format

Share Document