Good Laboratory Practice for optimization research

Kendall, Graham; Bai, Ruibin; Błażewicz, Jacek; Causmaecker, Patrick De; Gendreau, Michel; John, Robert; Li, Jiawei; McCollum, Barry; Pesch, Erwin; Qu, Rong; Sabar, Nasser R.; Berghe, Greet Vanden; Yee, Angelina Seow Voon

doi:10.1057/jors.2015.77

Cited by 71 publications

(38 citation statements)

References 87 publications

(86 reference statements)

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“…Indeed, since it takes long time to accumulate a sufficiently large pool of real-world data instances with representative parameter values and since important general insights into these parameters can be gained relatively early on, optimisation scientists create artificial benchmark data sets that mimic planning situations in practice (Otto, Otto, and Scholl 2013;Kendall et al 2016). Therefore, we formulate some findings for the data generation process suggested by our case study.…”

Section: Insights For Generation Of Artificial Data-sets In Comparisomentioning

confidence: 99%

Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding

Battini

Calzavara

Otto

et al. 2017

International Journal of Production Research

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In this paper, we advise to perform assembly line balancing simultaneously with decision-making on parts feeding. Such integrated planning may open additional potential to reduce labour costs. Additional planning flexibility gained with the integrated planning may be used to mitigate ergonomic risks at workplaces. We formulate the integrated assembly line balancing and parts feeding planning problem, propose a mixed-integer model and compare integrated planning to a common hierarchical planning approach in a detailed case study on the assembly of a self-priming pump. Our case study illustrates that workplaces with high ergonomic risks may emerge even in productions that involve handling parts and workpieces of low weights and avoid static and awkward postures. We also show that the proposed integrated planning approach may eliminate excessive ergonomic risks and improve productivity indicators simultaneously.

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Section: Insights For Generation Of Artificial Data-sets In Comparisomentioning

confidence: 99%

Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding

Battini

Calzavara

Otto

et al. 2017

International Journal of Production Research

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“…The model should be then tested using real data, see Kendall et al (2016). The availability of data is often problematic and, therefore, the model can be tested by running multiple scenarios, considering approximate data, or adjusting the available data (Watson et al, 2014).…”

Section: Prerequisites For Modellingmentioning

confidence: 99%

Prerequisites for the modelling of empty container supply chains

Kuźmicz

Pesch

2017

Engineering Management in Production and Services

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A B S T R A C T Containerisation of freight transport significantly facilitates the flow of traded goods between remote destinations. The most important container transport routes link Asia with North America and Europe. The seasonality and imbalance of trade are the main factors giving rise to problems related to empty container repositioning. The aim of this paper is to develop a concept of empty container supply chains and formulate prerequisites for its modelling in the search for the optimal solution with the help of linear programming and mixed integer programming methods. This paper indicates causes of the empty container relocation problem based on the literature analysis with a special focus on the Eurasian transportation route. Also, it provides a concept of empty container supply chain, prerequisites for its modelling and examples of container supply chains modelling presented in the literature. The main results of the paper include conceptualisation of an empty container supply chain and suggested modelling prerequisites. The paper contributes to research in the field of supply chain management and optimisation of transportation. K E Y W O R D S container transportation, supply chains, modelling, optimisation methods

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“…For the motives behind fraud and the measures needed to prevent it, see: Akerlof and Shiller (2015). 34 The concern for accuracy and reproducibility of computational experiments has intensified lately and has given rise to a very detailed and demanding proposal of protocols: Good Laboratory Practice (Kendall et al, 2016).…”

Section: Empirical Researchmentioning

confidence: 99%

Research into the area of supply chain

Corominas

2017

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Good Laboratory Practice for optimization research

Cited by 71 publications

References 87 publications

Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding

Preventing ergonomic risks with integrated planning on assembly line balancing and parts feeding

Prerequisites for the modelling of empty container supply chains

Research into the area of supply chain

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