Browsing by Author "Lokketangen, Arne"

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Citation - WoS: 44
Citation - Scopus: 52
A Tabu Search Approach for Buffer Allocation in Production Lines With Unreliable Machines
(Taylor & Francis Ltd, 2011) Demir, Leyla; Tunali, Semra; Lokketangen, Arne
The optimal allocation of buffers is an important research issue in designing production lines. In this study, a tabu search (TS) algorithm is proposed to find near-optimal buffer allocation plans for a serial production line with unreliable machines. The main objective is to maximize the production rate, i.e. throughput, of the line. The efficiency of the proposed method is also tested to solve buffer allocation problems with the objective of total buffer size minimization. To estimate the throughput of the line with a given specific buffer allocation, an analytical decomposition approximation method is used. The performance of the tabu search algorithm is demonstrated on existing benchmark problems. The results obtained by the TS algorithm are clearly encouraging, as the TS algorithm is much better than the other algorithms for all considered benchmark problems.
Citation - WoS: 15
Citation - Scopus: 18
Two Approaches for Solving the Buffer Allocation Problem in Unreliable Production Lines
(Pergamon-Elsevier Science Ltd, 2013) Demir, Leyla; Tunali, Semra; Eliiyi Türsel, Deniz; Lokketangen, Arne
This paper presents an integrated approach to solve the buffer allocation problem in unreliable production lines so as to maximize the throughput rate of the line with minimum total buffer size. The proposed integrated approach has two control loops; the inner loop and the outer loop. While the inner loop control includes an adaptive tabu search algorithm proposed by Demir et al. [8], binary search and tabu search are proposed for the outer loop. These nested loops aim at minimizing the total buffer size to achieve the desired throughput level. To improve the efficiency of the proposed tabu search, alternative neighborhood generation mechanisms are developed. The performances of the proposed algorithms are evaluated by extensive computational experimentation, and the results are reported. (C) 2013 Elsevier Ltd. All rights reserved.