Managing demand uncertainty in supply chain planning

Gupta, Amit Kumar; Maranas, Costas D.

doi:10.1016/s0098-1354(03)00048-6

Cited by 456 publications

(229 citation statements)

References 21 publications

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“…Many scholars endeavored to model the uncertainty in supply chains in recent times (e.g., Gupta and Maranas 2003;Santoso et al 2005;Alonso-Ayuso et al 2003;Kenne et al 2012). However, Pishvaee and Razmi (2012) implied that only the classical facility location models are implemented in real-world cases.…”

Section: Problem Statement and Modelingmentioning

confidence: 99%

The development of a green supply chain dual-objective facility by considering different levels of uncertainty

Khorasani

Almasifard

2017

J Ind Eng Int

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This paper presents a dual-objective facility programming model for a green supply chain network. The main objectives of the presented model are minimizing overall expenditure and negative environmental impacts of the supply chain. This study contributes to the existing literature by incorporating uncertainty in customer demand, suppliers, production, and casting capacity. An industrial case study is also analyzed to reveal the feasibility of the proposed model and its application. A fuzzy approach which is known as TH is used to solve the suggested dualobjective model. TH approach is integration of a max-min method (LH) and modified version of Werners' approach (MW). The outcome of this study reveals that the presented model can support green supply chain network in different levels of uncertainty. In presented model, cost and negative environmental impacts derived from the supply chain network will increase of higher levels of uncertainty.

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Section: Problem Statement and Modelingmentioning

confidence: 99%

The development of a green supply chain dual-objective facility by considering different levels of uncertainty

Khorasani

Almasifard

2017

J Ind Eng Int

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“…Practitioners are aware that uncertainty is inherent in processes with human-centered problems as stated by Sakawa et al [16], specifically for logistic and production operations by Gupta and Maranas [17], insisting on imprecision in information in production systems by Sevastijanov and Róg [18], as well as literature review of Mula et al [19].…”

Section: Closed Loop System Reviewmentioning

confidence: 99%

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Mehrsai

Karimi

Scholz‐Reiter

2012

Int J Adv Manuf Technol

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Nowadays, material planning and control strategies are becoming continuously complex tasks spanning from individual plants to logistic networks. In fact, this is the consequence of increasing intricacy in product variants and their respective convolution in networks' structures. Customers ask for specific products with individual characteristics that force companies for more clever performances by more flexibility. For doing so, the existing planning and control systems, which work based on central monitoring and controlling, show some limitations for organizing every operation on time or in the right time. Therefore, in the recent decade, a great attention is put on decentralized control and, to some extent, autonomy. This paper tries to investigate the possibility of combining this new research paradigm with existing strategies in production logistics, in order to improve material handling and control task according to material flow criteria. To show this, an exemplary plant after decoupling point out of a logistic network is considered for simulation and analysis. This combines Conwip system with learning autonomous pallets' concept in a discrete event simulation model. Several decentralized control scenarios are experimented and compared together. Here, the learn methodology is brought to pallets based on fuzzy rules and advantage of closed loop systems.

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“…Their model accounts for different cost items and tax laws associated with operations in different countries in order to maximize overall profit. For supply chains in which production sites are geographically diverse, transportation costs become significant [12]. In such cases, Guinet [11] shows that making production and transportation decisions simultaneously gives better results than making those decisions sequentially.…”

Section: Literature Reviewmentioning

confidence: 99%

Tactical level planning in float glass manufacturing with co-production, random yields and substitutable products

Taşkın

Ünal

2009

European Journal of Operational Research

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We investigate tactical level planning problems in float glass manufacturing. Float glass manufacturing is a process that has some unique properties such as uninterruptible production, random yields, partially controllable co-production compositions, complex relationships in sequencing of products, and substitutable products. Furthermore, changeover times and costs are very high, and production speed depends significantly on the product mix. These characteristics render measurement and management of the production capacity difficult.The motivation for this study is a real life problem faced at Trakya Cam in Turkey. Trakya Cam has multiple geographically separated production facilities. Since transportation of glass is expensive, logistics costs are high. In this paper, we consider multi-site aggregate planning, and color campaign duration and product mix planning. We develop a decision support system based on several mixed-integer linear programming models in which production and transportation decisions are made simultaneously. The system has been fully implemented, and has been in use at Trakya Cam since 2005.

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Managing demand uncertainty in supply chain planning

Cited by 456 publications

References 21 publications

The development of a green supply chain dual-objective facility by considering different levels of uncertainty

The development of a green supply chain dual-objective facility by considering different levels of uncertainty

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Tactical level planning in float glass manufacturing with co-production, random yields and substitutable products

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