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A GA-based approach for optimizing single-part flow-line configurations of RMS

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Abstract

Generating economical single-part flow-line (SPFL) configurations as candidates for a given demand period is an important optimization problem for reconfigurable manufacturing systems (RMS). The optimization problem addresses the questions of selecting number of workstations, number and type of paralleling identical machines as well as operation setups (OSs) for each workstation. The inputs include a precedence graph for a part, relationships between OSs and operations, machine options for each OS. The objective is to minimize the capital costs of the SPFL configurations. A 0–1 nonlinear programming (NLP) model is developed to handle the key issue of sharing machine utilization over consecutive OSs which is ignored in existing 0–1 integer linear programming (ILP) model. Then a GA-based approach is proposed to identify a set of economical solutions. To overcome the complexity of search space, a novel procedure is presented to guide GA to search within a refined solution space comprising the optimal configurations associated with feasible OS sequences. A case study shows that the best solution derived from the 0–1 NLP model through GA is better than the optimum of existing 0–1 ILP model. The results illustrate the effectiveness of our model and the efficiency of the GA-based approach.

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Abbreviations

B&B:

Branch-and-bound

CKSP:

Constrained K-shortest path

DAG:

Directed acyclic graph

DP:

Demand period

FOC:

Feasible OC sequence

FOS:

Feasible OS sequence

GA:

Genetic algorithm

ILP:

Integer linear programming

LP:

Linear programming

NLP:

Nonlinear programming

OC:

Operation cluster

OP:

Operation

OS:

Operation clusters setup

PG:

Precedence graph

RMS:

Reconfigurable manufacturing system

RMT:

Reconfigurable machine tool

SPFL:

Single-part flow-line

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Authors and Affiliations

  1. School of Mechanical Engineering, Southeast University, Nanjing, China

    Jianping Dou

  2. Key Laboratory of Measurement and Control of Complex Systems of Engineering, School of Automation, Ministry of Education, Southeast University, Nanjing, China

    Xianzhong Dai & Zhengda Meng

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  1. Jianping Dou
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  2. Xianzhong Dai
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  3. Zhengda Meng
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Correspondence to Jianping Dou.

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Dou, J., Dai, X. & Meng, Z. A GA-based approach for optimizing single-part flow-line configurations of RMS. J Intell Manuf 22, 301–317 (2011). https://doi.org/10.1007/s10845-009-0305-7

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  • DOI: https://doi.org/10.1007/s10845-009-0305-7

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