Supply chain design and cost analysis through simulation

Bottani, Eleonora; Montanari, Roberto

doi:10.1080/00207540902960299

Cited by 96 publications

(36 citation statements)

References 24 publications

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“…The relative importance of the globalization aspects has decreased while the number of papers devoted to environmental aspects and reverse (5) Altmann (2014), Brandenburg (2015), Cui (2015), Klibi and Martel (2012) Note: The number of papers for each specific problem is given in parenthesis. See key from Table 3.1 for abbreviations 3.4 Focus Areas for Supply Chain Configuration (7) Brandenburg (2015), Castellano et al (2013), Petridis (2015), Tian and Yue (2014), Tiacci et al (2014), You and Grossmann (2008), Zokaee et al (2014) ENV (9) Altmann ( (7) Baghalian et al (2013), Bassett and Gardner (2013), Habermann et al (2015), Hearnshaw and Wilson (2013), Klibi and Martel (2012), Madadi et al (2014), Mizgier et al (2015) RL (12) Amin and Zhang (2012), Chaabane et al (2012), Das and Rao Posinasetti (2015), Ghayebloo et al (2015), Kara and Onut (2010), Metta andBadurdeen (2013), Quariguasi Frota Neto et al (2008), Ramezani et al (2013), Ramezani et al (2014), Santibanez-Gonzalez and, Soleimani et al (2013), Vahdani and Naderi-Beni (2014) RP (6) Akanle and Zhang (2008), Bottani andMontanari (2010), Cheung et al (2012), Jamshidi et al (2015), Vanteddu et al (2011), You and…”

Section: Focus Areas For Supply Chain Configurationmentioning

confidence: 95%

Literature Review

Chandra¹,

Grabis²

2016

Supply Chain Configuration

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Section: Focus Areas For Supply Chain Configurationmentioning

confidence: 95%

Literature Review

Chandra¹,

Grabis²

2016

Supply Chain Configuration

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“…With regards to the input data used in this scenario, it should be mentioned that the average values are in line with typical figures of the moving consumer goods field (cf. Bottani and Montanari 2010). However, such data are not expected to represent any specific real system; rather, they are merely proposed as an example for validating the model developed in this paper.…”

Section: Mdpaeoq Validation Under Scenariomentioning

confidence: 96%

Investigating the demand propagation in EOQ supply networks using a probabilistic model

Montanari

Ferretti

Rinaldi

et al. 2014

International Journal of Production Research

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In this paper, we introduce a new demand probabilistic approach, named M.DPA.eoq (Montanari Demand Probabilistic Approach in economic order quantity [EOQ] scenario), for predicting the demand seen by an upper tier echelon (e.g. a distribution centre) of a supply network, serving several lower tier echelons operating according to an EOQ reorder policy. The M.DPA.eoq is based on an analytic approach, by which we derive the distribution of the demand seen by the upper tier echelon of the supply network. The approach has been designed to be very simple, so as to gain in pedagogical value. The simplicity and ease of application of this approach are confirmed by the possibility of exploiting general purpose software, such as Microsoft Excel TM , to implement and validate it. Moreover, the M.DPA.eoq has potential to be directly exploited by practitioners, such as supply network managers, to estimate the distribution of the demand the upper tier echelon will face under a defined network structure. Students and researchers could also benefit from such a model, given its ease of understanding and usage. With the purpose of showing its potential usefulness in real cases, we discuss two practical implications of the M.DPA.eoq, referring to the use of its results for: (1) computing the bullwhip effect of the network; and (2) analysing the impact of each retail store on the variance of the demand seen by the upper tier echelon.

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“…Analysis is centred on the evaluation of the effects of different configurations on the resulting total supply chain performance. Decision criteria that have been used include supply chains costs, the bullwhip effect, quality improvement initiatives, lead time reduction and environmental impacts (Bottani and Montannari 2010). MCDA is the predominant method used to support the green supply chain design decision-making, but there are some pilot investigations integrating MCDA and LCA for a more robust decision analysis.…”

Section: )mentioning

confidence: 99%

State-of-the-art sustainability analysis methodologies for efficient decision support in green production operations

Liu

Leat

Smith

2011

International Journal of Sustainable Engineering

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Over the last three decades, new concepts, strategies, frameworks and systems have been developed to tackle the sustainable development issue. This paper reviews the challenges, perspectives and recent advances in support of sustainable production operations decision-making. The aim of this review is to provide a holistic understanding of advanced scientific analysis methodologies for the evaluation of sustainability, to provide efficient decision support. Over 100 publications have been analysed, and a characterisation of state-of-the-art sustainability analysis methodologies has been produced, which includes life cycle assessment and multi-criteria decision analysis (MCDA), along with their applications to three key areas of production operations: sustainable design, sustainable manufacture and sustainable supply chain management. Distribution of existing work is discussed and future research directions are elicited from the literature. The paper finds three trends in supporting sustainable production operations decisions: (a) sustainability analysis has moved to whole life cycle assessment from single-stage assessment, (b) sustainability analysis has shifted away from single criterion to MCDA and (c) sustainability analysis has evolved from stand-alone approaches to integrated systematic methodologies. The paper concludes that integrated sustainability analysis can provide more efficient and effective support to complex decisionmaking in sustainable production operations.

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Supply chain design and cost analysis through simulation

Cited by 96 publications

References 24 publications

Literature Review

Literature Review

Investigating the demand propagation in EOQ supply networks using a probabilistic model

State-of-the-art sustainability analysis methodologies for efficient decision support in green production operations

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