Coordination of production and transportationin supply chain scheduling

Jun Pei; Panos M. Pardalos; Xinbao Liu; Wenjuan Fan; Shanlin Yang; Ling Wang

doi:10.3934/jimo.2015.11.399

Article Contents

2015, Volume 11, Issue 2: 399-419. Doi: 10.3934/jimo.2015.11.399

This issue Previous Article Simulation of the effects of different skill learning pathways in heterogeneous construction crews Next Article Recovery of the local volatility function using regularization and a gradient projection method

Coordination of production and transportation in supply chain scheduling

1.
School of Management, Hefei University of Technology, Hefei 230009
2.
Center for Applied Optimization, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611
3.
Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai 200444

Received: June 2013

Revised: March 2014

Published: April 2015

Abstract / Introduction Related Papers Cited by

Abstract

This paper investigates a three-stage supply chain scheduling problem in the application area of aluminium production. Particularly, the first and the third stages involve two factories, i.e., the extrusion factory of the supplier and the aging factory of the manufacturer, where serial batching machine and parallel batching machine respectively process jobs in different ways. In the second stage, a single vehicle transports jobs between the two factories. In our research, both setup time and capacity constraints are explicitly considered. For the problem of minimizing the makespan, we formalize it as a mixed integer programming model and prove it to be strongly NP-hard. Considering the computational complexity, we develop two heuristic algorithms applied in two different cases of this problem. Accordingly, two lower bounds are derived, based on which the worst case performance is analyzed. Finally, different scales of random instances are generated to test the performance of the proposed algorithms. The computational results show the effectiveness of the proposed algorithms, especially for large-scale instances.

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Mathematics Subject Classification: Primary: 90B35, 90C27; Secondary: 90C59.

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