A review of lot streaming in a flow shop environment with makespan criteria

[EN] Purpose: This paper reviews current literature and contributes a set of findings that capture the current state-of-the-art of the topic of lot streaming in a flow-shop. Design/methodology/approach: A literature review to capture, classify and summarize the main body of knowledge on lot streaming in a flow-shop with makespan criteria and, translate this into a form that is readily accessible to researchers and practitioners in the more mainstream production scheduling community. Findings: The existing knowledge base is somewhat fragmented. This is a relatively unexplored topic within mainstream operations management research and one which could provide rich opportunities for further exploration. Originality/value: This paper sets out to review current literature, from an advanced production scheduling perspective, and contributes a set of findings that capture the current state-of-the-art of this topic.This work has been carried out as part of the project “Programación de la Producción con Partición Ajustable de Lotes en entornos de Planificación mixta Pedido/Stock (PP-PAL-PPS)”, ref. GVA/2013/034 funded by Consellería de Educación, Cultura y Deportes de la Generalitat Valenciana.Gómez-Gasquet, P.; Segura Andrés, R.; Andrés Romano, C. (2013). A review of lot streaming in a flow shop environment with makespan criteria. Journal of Industrial Engineering and Management. 6(3):761-770. https://doi.org/10.3926/jiem.553S7617706

Permutation Flow Shop Scheduling unter Einbezug von Lot Streaming bei auftragsspezifischen Lieferterminvektoren für Due Window-bezogene Zielfunktionen

In dieser Arbeit wird eine Untersuchung vorgestellt zur Aufteilung von Auftragslosen mit mehreren identischen Einheiten in mehrere sog. Sublots, angewandt auf mehrere Liefertermine pro Auftrag. Hierfür werden zwei Zielsetzungen verfolgt, die Minimierung von Terminabweichungen sowie die Minimierung der nicht termingerecht fertiggestellten Menge. Diese Problemstellung wurde bislang in der Literatur nicht untersucht, hat aber praktische Relevanz in allen Fragestellungen, bei denen mehrere identische Einheiten zu fertigen und an verschiedenen Zeitpunkten auszuliefern sind. Die bisherige Forschung hat in den vergangenen knapp fünfzig Jahren die Aufteilung von Auftragslosen intensiv für die Problemstellung einer Minimierung der Gesamtdurchlaufzeit untersucht und hierzu eine Reihe optimierender wie heuristischer Verfahren vorgestellt. Es wurden in dieser Zeit jedoch nur wenige Untersuchungen unter Einbezug von Lieferterminzielsetzungen publiziert, welche zudem alle auf nur einen Liefertermin pro Auftrag ausgelegt waren. Es ist somit die Frage bislang offen geblieben, inwiefern eine Aufteilung von Aufträgen geeignet ist, mehrere Liefertermine pro Auftrag mit geringeren Terminabweichungen zu bedienen. In der vorliegenden Arbeit werden erstmalig auftragsspezifische Lieferterminvektoren und damit verbunden die Zuordnung von Sublots zu diesen Lieferterminen untersucht, angewandt auf Reihenfertigungsprozesse unter Einbezug von Maschinenrüstzeiten. Hierzu wird ein gemischt-ganzzahliges Modell zur Bestimmung der Sublot-Anzahlen sowie ihrer -Größen vorgestellt. Dieses setzt im Rahmen eines zweistufigen Lösungsverfahrens auf einer zuvor bestimmten Zuordnungsmatrix von Auftrags-Sublots in sog. Einlastungspositionen auf den Maschinen auf. Die Bestimmung der Positionen erfolgt zunächst mit Hilfe von Prioritätsregeln und wird durch ein heuristisches Verfahren in Form eines Genetischen Algorithmus anschließend verbessert. Das vorgestellte Verfahren wurde in einer numerischen Untersuchung validiert. In dieser konnte aufgezeigt werden, dass mit steigendem Rüstaufwand mehrere Liefertermine durch ein Sublot bedient werden, während die Zuordnung mehrerer Sublots zu einem Liefertermin abnahm. In allen Testinstanzen führte das Verfahren zu besseren Zielfunktionswerten im Vergleich zu einer Produktion ohne Aufteilung in Teillose. Mit der vorliegenden Arbeit wird die bisherige Forschung zu Lot Streaming um eine neue Richtung erweitert und ein neues Lösungsverfahren vorgestellt.The present thesis introduces a study concerning the splitting of jobs consisting of several identical items into sublots under the assumption of several due windows per job. The two objectives regarded are minimizing the time deviation from due windows and minimizing the number of parts not finished on time. This research question has not been addressed before, but is highly important for any practical situation in which several identical items have to be produced and delivered to customers in various time slots. Previous research within the past fifty years has focused intensively on splitting jobs into sublots to minimize the makespan. Therefore, optimizing and heuristic solution procedures were provided. During this time research involving due dates has received only little attention, which all focused on a single due date per job. Therefore the question remains open if splitting a job into sublots is appropriate to serve several due dates per job to reduce deviations from due dates. This thesis introduces for the first time several due windows per job und investigates the allocation of sublots to due windows, under the assumption of flow shop environments including setups. To achieve this, a mixed integer programming formulation is presented to simultaneously determine sublot number and sizes per job. This approach is based on a two-stage solution method which provides an allocation of job sublots into so-called dispatching positions on the machines in the first stage. The dispatchment of positions is firstly done by using priority rules and afterwards improved by a heuristic procedure based on a Genetic Algorithm. To prove the effectiveness of the proposed method, numerical examples were calculated. These experiments are presented to show that higher setup durations lead to more due windows being served by a single sublot, whereas the number of sublots serving only a single due window diminishes. All of the test instances prove the solution procedure presented in this thesis to be effective to reduce the objective function value compared to a production without using the splitting possibility. The present thesis extends the previously published work on lot streaming to a new research direction which has not been explored before

An estimation of distribution algorithm for lot-streaming flow shop problems with setup times

Lot-streaming flow shops have important applications in different industries including textile, plastic, chemical, semiconductor and many others. This paper considers an n-job m-machine lot-streaming flow shop scheduling problem with sequence-dependent setup times under both the idling and noidling production cases. The objective is to minimize the maximum completion time or makespan. To solve this important practical problem, a novel estimation of distribution algorithm (EDA) is proposed with a job permutation based representation. In the proposed EDA, an efficient initialization scheme based on the NEH heuristic is presented to construct an initial population with a certain level of quality and diversity. An estimation of a probabilistic model is constructed to direct the algorithm search towards good solutions by taking into account both job permutation and similar blocks of jobs. A simple but effective local search is added to enhance the intensification capability. A diversity controlling mechanism is applied to maintain the diversity of the population. In addition, a speed-up method is presented to reduce the computational effort needed for the local search technique and the NEH-based heuristics. A comparative evaluation is carried out with the best performing algorithms from the literature. The results show that the proposed EDA is very effective in comparison after comprehensive computational and statistical analyses.This research is partially supported by the National Science Foundation of China (60874075, 70871065), and Science Foundation of Shandong Province in China under Grant BS2010DX005, and Postdoctoral Science Foundation of China under Grant 20100480897. Ruben Ruiz is partially funded by the Spanish Ministry of Science and Innovation, under the project "SMPA-Advanced Parallel Multiobjective Sequencing: Practical and Theoretical Advances" with reference DPI2008-03511/DPI and by the IMPIVA-Institute for the Small and Medium Valencian Enterprise, for the project OSC with references IMIDIC/2008/137, IMIDIC/2009/198 and IMIDIC/2010/175.Pan, Q.; Ruiz García, R. (2012). An estimation of distribution algorithm for lot-streaming flow shop problems with setup times. Omega. 40(2):166-180. https://doi.org/10.1016/j.omega.2011.05.002S16618040

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe