scholarly journals DP-TABU: an algorithm to solve single-depot multi-line vehicle scheduling problem

2021 ◽  
Author(s):  
Zhao Xinchao ◽  
Sun Hao ◽  
Lu Juan ◽  
Li Zhiyu
Keyword(s):  
Public Transportation ◽  
Performance Optimization ◽  
Resource Sharing ◽  
Simulated Annealing Algorithm ◽  
Single Line ◽  
Scheduling Problem ◽  
Object A ◽  
Vehicle Operation ◽  
Service Object ◽  
Annealing Algorithm

AbstractA DP-TABU algorithm is proposed which can effectively solve the multi-line scheduling problem of single Deport (SD-ML-VSP). The multi-line regional coordinated dispatch of the single-line deport of the bus is to solve the problems of idle low-peak vehicles and insufficient peak capacity in single-line scheduling. The capacity of multiple lines at the same station is adjusted to realize resource sharing such as timetables, vehicles, and drivers. Shared capacity such as bus departure intervals and bus schedules. Taking the regional scheduling of multiple lines at the same station as the service object, a vehicle operation planning model based on the objective of optimal public transportation resources (minimum bus and driver costs) is established to optimize the vehicle dispatching mode of multiple lines. We applied this algorithm to the three lines S105, S107, and S159 of Zhengzhou Public Transport Corporation, and the results proved that the algorithm is effective. Through comparison with manual scheduling and simulated annealing algorithm, the advantages of DP-TABU algorithm in performance optimization and robustness are further verified.

scholarly journals A two-agent one-machine multitasking scheduling problem solving by exact and metaheuristics

2021 ◽  
Author(s):  
Chin-Chia Wu ◽  
Ameni Azzouz ◽  
Jia-Yang Chen ◽  
Jianyou Xu ◽  
Wei-Lun Shen ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Completion Time ◽  
Simulated Annealing Algorithm ◽  
Optimal Schedule ◽  
Computational Studies ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Large Size ◽  
Annealing Algorithm ◽  
One Machine

AbstractThis paper studies a single-machine multitasking scheduling problem together with two-agent consideration. The objective is to look for an optimal schedule to minimize the total tardiness of one agent subject to the total completion time of another agent has an upper bound. For this problem, a branch-and-bound method equipped with several dominant properties and a lower bound is exploited to search optimal solutions for small size jobs. Three metaheuristics, cloud simulated annealing algorithm, genetic algorithm, and simulated annealing algorithm, each with three improvement ways, are proposed to find the near-optimal solutions for large size jobs. The computational studies, experiments, are provided to evaluate the capabilities for the proposed algorithms. Finally, statistical analysis methods are applied to compare the performances of these algorithms.

Hybrid Method for Solving Flexible Open Shop Scheduling Problem with Simulated Annealing Algorithm and Multi-Agent Approach

2011 ◽  
Vol 383-390 ◽  
pp. 4612-4619 ◽  
Author(s):  
Tadeusz Witkowski ◽  
Paweł Antczak ◽  
Arkadiusz Antczak
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
The Other ◽  
Scheduling Problem ◽  
Open Shop Scheduling ◽  
Hand Search ◽  
Shop Scheduling ◽  
Multi Agent ◽  
Annealing Algorithm ◽  
Metaheuristic Optimization Algorithm

In this study we propose metaheuristic optimization algorithm, in which simulated annealing, multi agent approach with fuzzy logic are used. On the first level of solution search the multi agent approach is used, and on the second level – the simulated annealing. Two types of routing were considered: a serial and a parallel one. The multi-agent approach emphasizes flexibility rather than the optimality of solutions. On the other hand, search approaches such as simulated annealing, which focus more on the optimality of solutions.

scholarly journals Solving the Torpedo Scheduling Problem

2019 ◽  
Vol 66 ◽  
pp. 1-32
Author(s):  
Martin Josef Geiger ◽  
Lucas Kletzander ◽  
Nysret Musliu
Keyword(s):  
Material Flow ◽  
Simulated Annealing Algorithm ◽  
Steel Production ◽  
Experimental Investigations ◽  
Planning Problem ◽  
Scheduling Problem ◽  
Solution Approach ◽  
Annealing Algorithm ◽  
Problem Instances ◽  
Continuous Material

The article presents a solution approach for the Torpedo Scheduling Problem, an operational planning problem found in steel production. The problem consists of the integrated scheduling and routing of torpedo cars, i. e. steel transporting vehicles, from a blast furnace to steel converters. In the continuous metallurgic transformation of iron into steel, the discrete transportation step of molten iron must be planned with considerable care in order to ensure a continuous material flow. The problem is solved by a Simulated Annealing algorithm, coupled with an approach of reducing the set of feasible material assignments. The latter is based on logical reductions and lower bound calculations on the number of torpedo cars. Experimental investigations are performed on a larger number of problem instances, which stem from the 2016 implementation challenge of the Association of Constraint Programming (ACP). Our approach was ranked first (joint first place) in the 2016 ACP challenge and found optimal solutions for all used instances in this challenge.

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