A study of a two-stage flowshop assembly model with a truncated learning function

碩士 === 逢甲大學 === 統計學系統計與精算碩士班 === 107 === The two-stage three machines assembly scheduling problem has lots of applications in industrial production management. The topic of learning effects (or truncation based) has received growing attention in the field of scheduling. However, it is relatively une...

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Bibliographic Details
Main Authors: PAN,PO-AN, 潘柏安
Other Authors: Lin,Win-Chin
Format: Others
Language:zh-TW
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/handle/cxpjd8
Description
Summary:碩士 === 逢甲大學 === 統計學系統計與精算碩士班 === 107 === The two-stage three machines assembly scheduling problem has lots of applications in industrial production management. The topic of learning effects (or truncation based) has received growing attention in the field of scheduling. However, it is relatively unexplored in the two-stage three machines assembly problem. In this study, we thus investigated an assembly scheduling problem, with two machines in the first stage and an assembly machine in the second stage, together with a truncated learning function. The goal is to accomplish all jobs as soon as possible; i.e. to minimize the makespan. Owing to the NP-hardiness of the proposed problem, we derive some dominance propositions together with a lower bound for the branch-and-bound method for finding the optimal solution. In additional, six versions of hybrids greedy iterated algorithm, three versions of the local searches algorithm with and three versions without a probability scheme, are proposed. The local search methods include a pairwise interchange, an extraction and backward-shifted reinsertion, and an extraction and forward-shifted reinsertion. At last, the performance results, and statistical analysis of observations from the proposed algorithms are reported.