The time buffer approximated Buffer Allocation Problem: A row–column generation approach. (March 2020)

• Record Type: Journal Article
• Authors: Alfieri, Arianna; Matta, Andrea; Pastore, Erica
• Is Part Of: Computers & operations research. Volume 115(2020)
• Publication Date: 2020-03
• Subjects: Buffer allocation -- Simulation-optimization -- Assembly lines -- Math programming -- Row and column generation -- Exact method; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2019.104835
• Languages: English
• ISSNs: 0305-0548

Abstract

Highlights: Buffer Allocation Problem deals with finding the buffer size to reach a performance. Time-buffers are used in the paper to approximate the BAP problem. A row-column generation algorithm is proposed for the time-buffer BAP. The comparison with CPLEX shows the efficiency of the row-column generation. The model is able to solve the BAP for lines and assembly/disassembly systems. Abstract: One of the main problems in production systems is the buffer sizing. Choosing the right buffer size, at each production stage, that allows to achieve some performance measure (usually throughput or waiting time) is known as Buffer Allocation Problem (BAP), and it has been widely studied in the literature. Due to its complexity, BAP is usually approached using decomposition methods, under very strict system assumptions, or using simulation-optimization techniques. In this paper, the approximated mathematical programming formulation of the BAP simulation-optimization based on the time buffer concept is used. Using this approximation, buffers are modeled as temporal lags ( time buffers ) and this allows to use Linear Programming (LP) instead of Mixed Integer Linear Programming (MILP) models. Although LP models are easier to solve than MILPs, the huge dimension and the complex solution space topology of the time buffer approximated BAP call for ad hoc solution algorithms. To this purpose, a row-column generation algorithm is proposed, which exploits the theoretical properties of the time buffer approximation to reduce the solution time. The proposed algorithm has been compared with a standard LP solver (ILOG CPLEX) and with a state-of-the-art MILP solver and it proved to be better than the LP solver in most of the cases, and more robust than the MILP solver with respect to computation time. Moreover, the LP model (for flow lines) is able to solve the BAP also for assembly/disassembly lines.