Supply Chain Management: An Opportunity For Metaheuristics

Ramalhinho-Lourenço, Helena

doi:10.2139/ssrn.273425

Cited by 6 publications

(2 citation statements)

References 42 publications

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“…Forecasting in SCM is carried out by using a computerized system [10]. The author proposed metaheuristics based approach for SCM [11]. The author presented quantitative model using clustering for SCM [12].…”

Section: Literature Surveymentioning

confidence: 99%

Logistics Optimization in Supply Chain Management using Clustering Algorithms

Prabhu¹,

Hema²,

Chepure³

et al. 2020

SCPE

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Today's business environment, survival and making profit in market are the prime requirement for any enterprise due to competitive environment. Innovation and staying updated are commonly identified two key parameters for achieving success and profit in business. Considerably supply chain management is also accountable for profit. As a measure to maximize the profit, supply chain process is to be streamlined and optimized. Appropriate grouping of various suppliers for the benefit of shipment cost reduction is proposed. Data relating to appropriate attributes of supplier logistics are collected. A methodology is proposed to optimize the supplier logistics using clustering algorithm. In the proposed methodology data preprocessing, clustering and validation process have been carried out. The Z-score normalization is used to normalize the data, which converts the data to uniform scales for improving the clustering performance. By employing Hierarchical and K-means clustering algorithms the supplier logistics are grouped and performance of each method is evaluated and presented. The supplier logistics data from different country is experimented. Outcome of this work can help the buyers to select the cost effective supplier for their business requirements.

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Section: Literature Surveymentioning

confidence: 99%

Logistics Optimization in Supply Chain Management using Clustering Algorithms

Prabhu¹,

Hema²,

Chepure³

et al. 2020

SCPE

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“…For general treatises on scheduling, see Bhaskaran and Pinedo (1992), Brucker (1998), Pinedo (2002), and Pinedo and Chao (1999). For applications of scheduling to supply chain management, see Hall and Potts (2000) and Lourenco (2001). Some research has been done on more integrated models in the form of hierarchical planning systems; this research has resulted in frameworks that incorporate planning and scheduling; see Bowersox and Closs (1996), Barbarosoglu and Ozgur (1999), Dhaenens-Flipo and Finke (2001), Shapiro (2001), andMiller (2002).…”

Section: Introductionmentioning

confidence: 99%

Planning and Scheduling in Supply Chains: An Overview of Issues in Practice

Kreipl

Pinedo

2004

Production and Operations Management

172

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This paper gives an overview of the theory and practice of planning and scheduling in supply chains. It first gives an overview of the various planning and scheduling models that have been studied in the literature, including lot sizing models and machine scheduling models. It subsequently categorizes the various industrial sectors in which planning and scheduling in the supply chains are important; these industries include continuous manufacturing as well as discrete manufacturing. We then describe how planning and scheduling models can be used in the design and the development of decision support systems for planning and scheduling in supply chains and discuss in detail the implementation of such a system at the Carlsberg A/S beerbrewer in Denmark. We conclude with a discussion on the current trends in the design and the implementation of planning and scheduling systems in practice.

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