scholarly journals Fitness Distance Correlation Strategy for Solving the RGV Dynamic Scheduling Problem

Author(s):  
Wei Li ◽  
Furong Tian ◽  
Ke Li

Rail guide vehicle (RGV) problems have the characteristics of fast running, stable performance, and high automation. RGV dynamic scheduling has a great impact on the working efficiency of an entire automated warehouse. However, the relative intelligent optimization research of different workshop components for RGV dynamic scheduling problems are insufficient scheduling in the previous works. They appear idle when waiting, resulting in reduced operating efficiency during operation. This article proposes a new distance landscape strategy for the RGV dynamic scheduling problems. In order to solve the RGV dynamic scheduling problem more effectively, experiments are conducted based on the type of computer numerical controller (CNC) with two different procedures programming model in solving the RGV dynamic scheduling problems. The experiment results reveal that this new distance landscape strategy can provide promising results and solves the considered RGV dynamic scheduling problem effectively.

2018 ◽  
Vol 11 (3) ◽  
pp. 390 ◽  
Author(s):  
Basar Ogun ◽  
Çigdem Alabas-Uslu

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem is addressed to provide on-time completion of customer orders in the environment of lean manufacturing. The problem is to optimize partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components.Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid from inventory of final products. The first model is a non-linear integer programming model while the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented.Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times comparing to the other two models. It was also showed that the alternative model can solve moderate sized real-world problems.Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature since it includes new circumstances which may arise in real-world applications. This research, also, contributes the literature of batch scheduling problem by presenting new optimization models.


2013 ◽  
Vol 380-384 ◽  
pp. 4775-4781
Author(s):  
Ji Feng Qian ◽  
Xiao Ning Zhu ◽  
Zhan Dong Liu

In order to improve the efficiency of the handling operations equipment in container terminal, reduce the waiting time of container ship in Port, this paper researches the integrated scheduling of the different types of handling equipment in container terminal, considers the constraints of different handling equipment impact between each other, build a mixed integer programming model, presents a heuristic algorithm for the of the scheduling problem and gets the approximate solution. The results show that the integrated scheduling can effectively reduce the time of the ship staying in port, and improve the overall operating efficiency of the port.


2008 ◽  
Vol 07 (02) ◽  
pp. 249-252 ◽  
Author(s):  
HELAN LIANG ◽  
SUJIAN LI

Focusing on the limitations of the traditional Continuous Casting-Direct Hot Charge Rolling (CC-DHCR) planning and scheduling methods that rarely consider dynamic scheduling problems, a new method is put forward. The key idea is to make out clusters and integrated plans in the planning layer, and then to adjust the rolling sequences according to the slab cluster-based strategy in the dynamic scheduling layer. Results of the test with data from practical production process show that the method can effectively solve the CC-DHCR planning and scheduling problem and increase the DHCR ratio.


Author(s):  
Guei-Hao Chen ◽  
Jyh-Cherng Jong ◽  
Anthony Fu-Wha Han

Crew scheduling is one of the crucial processes in railroad operation planning. Based on current regulations and working and break time requirements, as well as the operational rules, this process aims to find a duty arrangement with minimal cost that covers all trips. Most past studies considered this subject for railroad systems as an optimization problem and solved it with mathematical programming-based methods or heuristic algorithms, despite numerous logical constraints embedded in this problem. Few studies have applied constraint programming (CP) approaches to tackle the railroad crew scheduling problem. This paper proposes a hybrid approach to solve the problem with a CP model for duty generation, and an integer programming model for duty optimization. These models have been applied to the Kaohsiung depot of Taiwan Railways Administration, the largest railroad operator in Taiwan. The encouraging results show that the proposed approach is more efficient than the manual process and can achieve 30% savings of driver cost. Moreover, the approach is robust and provides flexibility to easily accommodate related operational concerns such as minimizing the number of overnight duties. Thus, this hybrid two-phase approach seems to have the potential for applications to the railroad crew scheduling problems outside Taiwan.


2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Hao Xu ◽  
Yue Zhao ◽  
Li-Ning Xing ◽  
You Zhou

The data transmission dynamic scheduling is a process that allocates the ground stations and available time windows to the data transmission tasks dynamically for improving the resource utilization. A novel heuristic is proposed to solve the data transmission dynamic scheduling problem. The characteristic of this heuristic is the dynamic hybridization of simple rules. Experimental results suggest that the proposed algorithm is correct, feasible, and available. The dynamic hybridization of simple rules can largely improve the efficiency of scheduling.


Author(s):  
Valentin Cristea ◽  
Ciprian Dobre ◽  
Corina Stratan ◽  
Florin Pop

This chapter presents the scheduling problem in large scale distributed systems. Most parts of the chapter are devoted to discussion of scheduling algorithms and models. The main challenges of scheduling problem are approached here. The implementation issues are also covered. The chapter has three parts. The first part covers basics like scheduling models, scheduling algorithms for independent tasks and DAG scheduling Algorithms for tasks with dependencies. The first part of the chapter presents a classification of scheduling problems, methods that are relevant for the solution procedures, and computational complexity. The scheduling models are presented based on systems architecture described in Resource Management chapter. This firs part also provides a critical analysis of most important algorithms from different points of view, such as static versus dynamic policies, objective functions, applications models, adaptation, QoS constraints and strategies dealing with dynamic behavior of resources. The second part covers new scheduling mechanism like resources co-allocation and advance reservation. Multi-criteria optimization mechanisms for users and systems constrain (e.g. load-balancing, minimization of execution time) are described and analyzed in this chapter. This part uses algorithm and methods to highlight the importance of these topics. The dynamic scheduling is also the subject of this part. It is also presented the implementation issues for scheduler tools. Since it is not possible to cover the whole area of scheduling in one chapter, some restrictions are imposed. Firstly, the chapter presents only Scheduling for Large Scale Distributed Systems (LSDS), without single system scheduling. Secondly, some interesting topics of fault tolerance (re-scheduling) are not analyzed in this chapter.


2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Qiu Dishan ◽  
He Chuan ◽  
Liu Jin ◽  
Ma Manhao

Focused on the dynamic scheduling problem for earth-observing satellites (EOS), an integer programming model is constructed after analyzing the main constraints. The rolling horizon (RH) strategy is proposed according to the independent arriving time and deadline of the imaging tasks. This strategy is designed with a mixed triggering mode composed of periodical triggering and event triggering, and the scheduling horizon is decomposed into a series of static scheduling intervals. By optimizing the scheduling schemes in each interval, the dynamic scheduling of EOS is realized. We also propose three dynamic scheduling algorithms by the combination of the RH strategy and various heuristic algorithms. Finally, the scheduling results of different algorithms are compared and the presented methods in this paper are demonstrated to be efficient by extensive experiments.


2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Junjie Chen ◽  
Shurong Tong ◽  
Hongmei Xie ◽  
Yafei Nie ◽  
Jingwen Zhang

In resource-constrained project scheduling problems, renewable resources can be expanded into human resources with competency differences. A flexible resource-constrained project scheduling problem with competency differences is proposed, which is a practical extension close to Research and Development (R&D) program management, from the traditional multimode resource-constrained project scheduling problem. A parameter and estimation formula to measure staff competency is presented, and a mixed-integer programming model is established for the problem. The single-objective optimization problems of optimal duration and optimal cost are solved sequentially according to the biobjective importance. To solve the model, according to the assumptions and constraints of the model, the initial network diagram of multiple projects is determined, the enumeration algorithm satisfying constraint conditions provides the feasible solution sets, and the algorithm based on dynamic programming is designed for phased optimization. Experimental results show that the proposed optimization model considering competence differences can solve the problem effectively.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Shujin Qin ◽  
Shixin Liu ◽  
Hanbin Kuang

Workforce scheduling is an important and common task for projects with high labour intensities. It becomes particularly complex when employees have multiple skills and the employees’ productivity changes along with their learning of knowledge according to the tasks they are assigned to. Till now, in this context, only little work has considered the minimum quality limit of tasks and the quality learning effect. In this research, the workforce scheduling model is developed for assigning tasks to multiskilled workforce by considering learning of knowledge and requirements of project quality. By using piecewise linearization to learning curve, the mixed 0-1 nonlinear programming model (MNLP) is transformed into a mixed 0-1 linear programming model (MLP). After that, the MLP model is further improved by taking account of the upper bound of employees’ experiences accumulation, and the stable performance of mature employees. Computational experiments are provided using randomly generated instances based on the investigation of a software company. The results demonstrate that the proposed MLPs can precisely approach the original MNLP model but can be calculated in much less time.


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