A tabu search algorithm for simultaneous machine/AGV scheduling problem

Yan Zheng, Yujie Xiao, Yoonho Seo

Research output: Contribution to journalArticlepeer-review

80 Citations (Scopus)


Machines and automated guided vehicles (AGVs) scheduling problems are two essential issues that need to be addressed for the efficiency of the overall production system. The purpose of this paper is to study the simultaneous scheduling problem of machines and AGVs in a flexible manufacturing system (FMS) since the global optimum cannot be reached by considering each of them individually. In this paper, a mixed integer linear programming (MILP) model is developed with the objective of makespan minimisation. The MILP model consists of the following two constraint sets: machines and AGVs scheduling sub-problems. As both sub-problems are known to be NP-hard, a heuristic algorithm based on tabu search (TS) is proposed to get optimal or near to optimal solution for large-size problems within reasonable computation time. The proposed algorithm includes a novel two-dimensional solution representation and the generation of two neighbour solutions, which are alternately and iteratively applied to improve solutions. Moreover, an improved lower bound calculation method is introduced for the large-size problems. Computational results show the superior performance of the TS algorithm for the simultaneous scheduling problem.

Original languageEnglish
Pages (from-to)5748-5763
Number of pages16
JournalInternational Journal of Production Research
Issue number19
Publication statusPublished - 2014


  • AGVs scheduling
  • machines scheduling
  • simultaneous scheduling
  • tabu search

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


Dive into the research topics of 'A tabu search algorithm for simultaneous machine/AGV scheduling problem'. Together they form a unique fingerprint.

Cite this