Online Demand Fulfillment Under Limited Flexibility

Xu, Zhen; Zhang, Hailun; Zhang, Jiheng; Zhang, Rachel Quan

doi:10.1287/mnsc.2019.3449

Cited by 18 publications

(9 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the special case of the long chain with identical demand arrival probabilities, the bound by Xu et al. (2019) is

O (m^{2})

, which is slightly better than the bound by Asadpour et al. (2018) that is

O (m^{2} \ln m)

.…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 73%

“…which is a bounded loss independent of the total market size K. The above bound becomes worse as the number of resources m increases, and the bound improves as the slack ξ becomes larger. In the special case of the long chain with identical demand arrival probabilities, the bound by Xu et al (2019) is Oðm 2 Þ, which is slightly better than the bound by Asadpour et al (2018) that is Oðm 2 ln mÞ.…”

Section: Online Resource Allocation: Online Allocations + Lost Demandmentioning

confidence: 93%

“…More recently, Xu et al. (2019) generalize the model and results in Asadpour et al. (2018) by considering a general flexibility design

scriptA

that satisfies the GCG condition (19).…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 99%

“…Xu et al. (2019) prove that for any flexibility design with a positive GCG ξ > 0, the expected total lost sales under LDP is bounded from above by

\ln 64 \cdot max \{\frac{1}{q_{truemin}}, \frac{m}{ξ}\},

which is a bounded loss independent of the total market size K . The above bound becomes worse as the number of resources m increases, and the bound improves as the slack ξ becomes larger.…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 99%

“…(2018) and Xu et al. (2019) considered a single item setting where each arriving request demands exactly one unit of inventory from any resource that is able to serve this request. Moreover, the model studied in both papers do not explicitly account for the costs

c_{ij}

associated with fulfilling a type j request by using resource i (e.g., in the context of online retailing,

c_{ij}

could be the transportation cost of delivering the order from distribution center i to demand region j .)…”

Section: Future Research Directions and Concluding Remarksmentioning

confidence: 99%

See 4 more Smart Citations

A Review of Flexible Processes and Operations

Wang

Zhang

2021

Production and Operations Management

View full text Add to dashboard Cite

O ne effective means to hedge against uncertainty and better match supply with demand in a swiftly changing environment is to adopt a flexible operations strategy that allows timely response to realized demand. The notion of flexible processes and operations has led to significant impact on the performance of many manufacturing and service applications. However, investing a fully flexible system is usually prohibitively expensive with overwhelming implementation complexity and overhead. As a result, the search for efficient system designs with only a limited amount of flexibility but can capture the majority of the benefits achieved by a fully flexible system has been an active research question in the operations literature. Fortunately, it has been widely observed that even just a small amount of flexibility, if configured in a right way, can be extremely effective in hedging against demand uncertainty and mitigating supply-demand mismatch. In this review, we shall present and discuss some recent developments in flexible operations over the past decade. We organize our review into models with independent and dependent capacity allocation decisions across time periods. In the former setting, capacity allocation decisions in one period do not affect future demand fulfillment decisions and one can start over every period as if one is dealing with a single-period model, whereas in the latter case capacity allocation decisions in one period would have an impact on the decisions in future periods. The review concludes with some discussions about topics for future research exploration.

show abstract

“…In the special case of the long chain with identical demand arrival probabilities, the bound by Xu et al. (2019) is

O (m^{2})

, which is slightly better than the bound by Asadpour et al. (2018) that is

O (m^{2} \ln m)

.…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 73%

Section: Online Resource Allocation: Online Allocations + Lost Demandmentioning

confidence: 93%

“…More recently, Xu et al. (2019) generalize the model and results in Asadpour et al. (2018) by considering a general flexibility design

scriptA

that satisfies the GCG condition (19).…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 99%

“…Xu et al. (2019) prove that for any flexibility design with a positive GCG ξ > 0, the expected total lost sales under LDP is bounded from above by

\ln 64 \cdot max \{\frac{1}{q_{truemin}}, \frac{m}{ξ}\},

which is a bounded loss independent of the total market size K . The above bound becomes worse as the number of resources m increases, and the bound improves as the slack ξ becomes larger.…”

Section: Models With Dependent Capacity Allocations Across Time Periodsmentioning

confidence: 99%

c_{ij}

associated with fulfilling a type j request by using resource i (e.g., in the context of online retailing,

c_{ij}

could be the transportation cost of delivering the order from distribution center i to demand region j .)…”

Section: Future Research Directions and Concluding Remarksmentioning

confidence: 99%

See 3 more Smart Citations

A Review of Flexible Processes and Operations

Wang

Zhang

2021

Production and Operations Management

View full text Add to dashboard Cite

show abstract

Capacity and resource allocation in flexible production networks by a game theory model

Renna

2022

Int J Adv Manuf Technol

View full text Add to dashboard Cite

In many production applications, plants that produce multiple products with random demands share the required items among suppliers. The decision of how to allocate requests between suppliers to achieve the desired level of customer service is relevant to the efficiency of the production network. The literature highlighted how the long chain has the same level of performance as the full flexible network. This research proposes a decision model based on the game theory model to improve the performance of the production network. The model uses the Gale-Shapley algorithm with low computational complexity to share the demand among the suppliers. A simulation environment allows the evaluation of the proposed model in different conditions, and the model is compared to the dedicated, full flexibility, and long chain models. The numerical results show how the proposed model improves the efficiency of the production environment by keeping the number of connections with the supplier closer to the long chain model.

show abstract

Process flexibility in the presence of product modularity: Does modularity help?

Verma

Chatterjee

2023

International Journal of Production Economics

View full text Add to dashboard Cite

Online Demand Fulfillment Under Limited Flexibility

Cited by 18 publications

References 32 publications

A Review of Flexible Processes and Operations

A Review of Flexible Processes and Operations

Capacity and resource allocation in flexible production networks by a game theory model

Process flexibility in the presence of product modularity: Does modularity help?

Contact Info

Product

Resources

About