Polynomial-time solvable cases of the capacitated multi-echelon shipping network scheduling problem with delivery deadlines

Wang, Gang; Lei, Lei

doi:10.1016/j.ijpe.2012.02.006

Cited by 27 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After sales forecasts and resource requirements, the various alternate production plans are generated Liu et al, 2011;Mirapour et al, 2011;Li et al, 2013). Additionally, SCA provides useful insights to problems related to operations scheduling problems, which can be formulated as mixed integer linear programming problems (Wang and Lei, 2012;. In routing problems, SCA can help in e.g.…”

Section: Productionmentioning

confidence: 99%

“…SCA can also help in predicting accurately inventory needs and in responding to changing customer demands, utilizing statistical forecasting techniques Wei et al, 2011), as well as to reducing dramatically inventory costs . Additionally, SCA is applied to address problems that occur within multi-echelon distribution networks (Wang and Lei, 2012;He and Zhao, 2012). It determines the appropriate inventory levels while taking under consideration factors such as demand variability at the network nodes as well as performance (e.g., lead time, delays, and service level) Guo and Li, 2014).…”

Section: Inventorymentioning

confidence: 99%

See 1 more Smart Citation

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

Self Cite

1,076

750

View full text Add to dashboard Cite

The amount of data produced and communicated over the Internet is significantly increasing, thereby creating challenges for the organizations that would like to reap the benefits from analyzing this massive influx of big data. This is because big data can provide unique insights into, inter alia, market trends, customer buying patterns, and maintenance cycles, as well as into ways of lowering costs and enabling more targeted business decisions. Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) -that we define as supply chain analytics (SCA), based on the nature of analytics (descriptive, predictive, prescriptive) and the focus of the LSCM (strategy and operations). To assess the extent to which SCA is applied within LSCM, we propose a maturity framework of SCA, based on four capability levels, that is, functional, process-based, collaborative, agile SCA, and sustainable SCA. We highlight the role of SCA in LSCM and denote the use of methodologies and techniques to collect, disseminate, analyze, and use big data driven information. Furthermore, we stress the need for managers to understand BDBA and SCA as strategic assets that should be integrated across business activities to enable integrated enterprise business analytics. Finally, we outline the limitations of our study and future research directions.

show abstract

Section: Productionmentioning

confidence: 99%

Section: Inventorymentioning

confidence: 99%

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Wang

Gunasekaran

Ngai

et al. 2016

International Journal of Production Economics

Self Cite

1,076

750

View full text Add to dashboard Cite

show abstract

“…The authors have analyzed computational complexity of various cases of the problem and have developed heuristics for NP-hard cases. [5] considered the problem of operations scheduling for capacitated multiechelon shipping network with delivery deadlines, where semi-finished goods are shipped from suppliers to customers through processing centers, with the objective of minimizing the shipping and penalty cost. The three polynomial-time solvable cases of this problem were reported: with identical order quantities; with designated suppliers; and with divisible customer order sizes.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Consequently, individual enterprises focus on developing their core capabilities and outsource non-core affairs to other partners or suppliers with different professional capabilities to upgrade their competitive advantage by applying these external and special sources and technology knowledge. In any supplier selection process, generally six main decision processes takes place viz: (1) make or buy, (2) supplier selection, (3) contract negotiation, (4) design collaboration, (5) procurement, and (6) sourcing analysis. Of these six decision process, supplier selection is one of the most vital and crucial decision and becomes more important when an organization has to select the supplier for more than one period and when the supplier's capacity, their quality level, lead time, and various cost parameters also vary.…”

Section: Introductionmentioning

confidence: 99%

Incorporating carbon penalties into supplier selection in the supply chain

Gandhi¹,

Galar²,

Jha³

2014

Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

View full text Add to dashboard Cite

A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos.Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da instituição detentora da supramencionada licença.Ao utilizador é apenas permitido o descarregamento para uso pessoal, pelo que o emprego do(s) título(s) descarregado(s) para outro fim, designadamente comercial, carece de autorização do respetivo autor ou editor da obra.Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. Incorporating carbon penalties into supplier selection in the supply chain Autor(es):Gandhi, Kanika; Galar, Diego; Jha, P. C. Publicado por:Imprensa Abstract-Supply chain management (SCM) practices have flourished since the 1990s. Enterprises realize that a large amount of direct and indirect cost can be managed from effective and efficient SCM practices. Supplier selection has great impact on integration of the supply chain relationship. Effective and accurate supplier selection decisions are significant components for procurement and distribution management in many firms to enhance their organizational performance. In this study a multiple sourcing procurement distribution optimization problem is considered. Three objective functions are minimization of costs, maximization of performance and minimization of carbon emission penalty cost respectively. In order to solve the problem, a fuzzy mathematical model and a fuzzy goal programming solution approach are proposed to satisfy the decision maker's aspirations for fuzzy goals. A real life case study is given to illustrate how the model is utilized.

show abstract

“…It has also been demonstrated how they can help in handling the most complex retail, wholesale, and multichannel challenges in inventory management, 11 as well as predict inventory needs in case of fluctuating customer demands through statistical forecasting techniques 12 and in reducing inventory costs. 13 Data could be used to define stocks in multiechelon distribution networks [14][15][16] and define the right inventory level in terms of demand variability at the network nodes, 17,18 which also helps in defining the appropriate safety stock level. 19,20 In addition to supply chains, other industrial data structures could be represented as networks and analyzed through the related measures.…”

Section: Introductionmentioning

confidence: 99%

A network perspective on the visualization and analysis of bill of materials

Cinelli

Ferraro

Iovanella

et al. 2017

International Journal of Engineering Business Management

View full text Add to dashboard Cite

A bill of materials (BoM), or product structure, is a diagram that lists all the components and parts required to produce one unit of a finished product, or end part. It is often represented as a tree structure with hierarchical relationships among different components and materials. In this article, we introduce two procedures to convert single and multiple BoM into networks. These procedures allow us to leverage the potentialities of networks analysis, providing new perspectives in terms of representation and extractable informative content, and thus gaining insights into the criticalities of parts and components. We conclude interpreting some network measures and their outcomes in terms of practical implications in industrial management, for example, product functional design and, above all, variety reduction programs.

show abstract

Polynomial-time solvable cases of the capacitated multi-echelon shipping network scheduling problem with delivery deadlines

Cited by 27 publications

References 22 publications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Big data analytics in logistics and supply chain management: Certain investigations for research and applications

Incorporating carbon penalties into supplier selection in the supply chain

A network perspective on the visualization and analysis of bill of materials

Contact Info

Product

Resources

About