Auction-theoretic coordination of production planning in the supply chain

Ertoğral, Kadir; Wu, S. David

doi:10.1080/07408170008967451

Cited by 92 publications

(67 citation statements)

References 14 publications

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“…These decisions are interrelated because one decision affects the outcome of another. It has been quite acknowledged that, whereas centralized approaches are theoretically better in pursuing global system performance, they have several drawbacks concerning operational costs, reliability, inventory costs and so forth (Ertogral, 2000). This is the reason why several researchers offer to use decentralized approaches for distributed production planning.…”

Section: Introductionmentioning

confidence: 99%

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Khalili‐Damghani¹,

Ghasemi²

2016

Industrial Engineering and Management Systems

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Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multiproduct supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship. .

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Section: Introductionmentioning

confidence: 99%

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Khalili‐Damghani¹,

Ghasemi²

2016

Industrial Engineering and Management Systems

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“…The advantages of these decentralized production systems can be cost reduction, efficiency improvement or also quick reaction to market changes even though more coordination effort is needed. Ertogral and David Wu (2000) showed that monolithic models, which use centralized decision schemes, should not be used in decentralized environments. Therefore, Cao and Chen (2006) proposed a bilevel model for plant selection in decentralized production environments.…”

Section: Introductionmentioning

confidence: 99%

Methodological Advances and New Formulations for Bilevel Network Design Problems

Fontaine

2018

Operations Research Proceedings

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“…A bidding procedure can be processed to obtain good resource allocation solutions using the CNP framework (e.g., [8,10]). …”

Section: Introductionmentioning

confidence: 99%

Design of Protocols for Task Administration in Collaborative Production Systems

Ko¹,

Nof²

2010

INT J COMPUT COMMUN

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Abstract:Customer-focused and concurrent engineering service systems process tasks more effectively as a result of the power of collaboration among multiple participants. In such environments, however, complex situations might arise that require decisions beyond simple coordination.Task Administration Protocols (TAPs) are designed as a control mechanism to manage complex situations in collaborative task environments. This article presents the design of TAPs for collaborative production systems in which tasks are performed by the collaboration of multiple agents. Three component protocols are found to constitute TAPs and are triggered at appropriate stages in task administration: 1) Task Requirement Analysis Protocol, 2) Shared Resource Allocation Protocol, and 3) Synchronization & Time-Out Protocol. A case study with TAPs metrics for task allocation in a collaborative production system is investigated to compare performance under TAPs, and under a non-TAP coordination protocol (which is considered to be simpler). In terms of task allocation ratio, the case study indicates that performance under TAPs is significantly better (up to 10.6%) than under the non-TAP coordination protocol, especially under medium or high load conditions. The advantage of TAPs can be explained by their design with relatively higher level of collaborative intelligence, addressing more complex control logic compared with non-TAP coordination protocols.

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Auction-theoretic coordination of production planning in the supply chain

Cited by 92 publications

References 14 publications

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Methodological Advances and New Formulations for Bilevel Network Design Problems

Design of Protocols for Task Administration in Collaborative Production Systems

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