Multi-level two-way cross-chain inventory coordination model that combines the same level with different levels in multi-supply chains

Yan, Bo; Cai, Congyan; Shi, Ping

doi:10.1177/0037549717706169

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…Yan et al 16 simulated the SC in a cluster network system where they consider the coordination of a cross-docking based on two individual SCs; they used the simulation software of dynamic systems Vensim ® . Moreover, they proposed a model to coordinate and optimize the multi-level cross-chain inventory with the objective of improving the customer satisfaction rate and the stock level.…”

Section: Literature Reviewmentioning

confidence: 99%

Relocation of the distribution center of a motor oil producer reducing its storage capacity: A case study

2019

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Enterprises face the challenge of identifying, following, and controlling the performance of their processes in the whole supply chain (SC) to guarantee an adequate level of service to the client. Since the delivery of orders on time has a direct impact in the client’s satisfaction, the managers of the SC face the challenge of choosing the best location, number, and capacity of the facilities to deliver the client’s orders on time. In this paper, we address a facility relocation problem. A motor oil manufacturing company currently has a distribution center (DC) with 17,800 storage locations and 20 docks for loading and unloading, operated traditionally, and it wishes to relocate the DC to a smaller one of 10,800 storage locations operated in an automated way. However, they do not have the certainty that the relocated DC will support the distribution logistics operation to deliver the clients’ orders on time. In this research, we make a feasibility analysis of the distribution logistics operation when relocating the DC through a simulation model. For that, it was essential to analyze the main storage and distribution processes of the new DC. The main contribution of this work is the development of a simulation model that can be used to analyze the feasibility of relocating a warehouse or DC to a specific location; the model establishes the main key performance indicators that must be evaluated in the simulation. The results of the simulation show that it is feasible to implement the relocation.

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Section: Literature Reviewmentioning

confidence: 99%

Relocation of the distribution center of a motor oil producer reducing its storage capacity: A case study

2019

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“…The frequent interactions of entities within IC can increase competition and improve coordination, efficiency and innovation, along with improvement in trust among supply chain partners. Yan et al (2017) investigated a cross-chain inventory emergency replenishment model including the entities of the supply chain such as manufacturers and retailers with the goal of increasing the customers’ satisfaction and keep it at an acceptable level. In nations such as Germany, India, USA and Italy, the growth of ICs has a significant role in feeding their product development and honing their capability so as to compete effectually in the global zone (DeWitt et al , 2006).…”

Section: Introductionmentioning

confidence: 99%

A practical supply-demand hub in industrial clusters: a new perspective

Kayvanfar

Husseini

Zhang

et al. 2019

MRR

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Purpose This paper aims to optimize the interactions of businesses located within industrial clusters (ICs) by using a supply-demand hub in ICs (SDHIC) as a conjoint provider of logistics and depository facilities for small- and medium-sized enterprises (SMEs) as producers, where all of these interactions are under supervision of a third-party logistics provider (3PL). Design/methodology/approach To evaluate the values of SDHIC, three mathematical models are proposed, optimally solved via GAMS and then compared. Also, a “linear relaxation-based heuristic” procedure is proposed to yield a feasible initial solution within a significant shorter computational time. To illustrate the values of SDHIC, comprehensive calculations over a case study and generated sets of instances are conducted, including several sensitivity analysis. Findings The experimental results demonstrate the efficiency of SDHIC for SMEs via combining batches and integrating the holding space of inventories, while the outcomes of the case study are aligned with those obtained from random sample examples, which confirms the trueness of used parameters and reveals the applicability of using SDHIC in real world. Finally, several interesting managerial implications for practitioners are extracted and presented. Practical implications Some of the managerial and practical implications are optimizing interactions of businesses involved in a supply chain of an IC containing some customers, suppliers and manufacturers and rectifying the present noteworthy gaps pertaining to the previously published research via using real assumptions and merging upstream and downstream of the supply chain through centralizing on storage of raw materials (supply echelon) and finished products (demand echelon) at the same place simultaneously to challenge a classic concept in which supply and demand echelons were being separately planned regarding their inventory management and logistics activities and showing the positive consequences of such challenge, showing the performance improvement of the proposed model compared to the classic model, by increasing the storing cost of raw materials and finished products, considering some disadvantages of using SDHIC and showing the usefulness of SDHIC in total, presenting some applied findings according to the obtained results of sensitivity analysis. Originality/value The key contributions of this paper to the literature are suggesting a new applied mathematical methodology to the supply chain (SC) of ICs by means of a conjoint provider of warehousing activities called SDHIC, comparing the new proposed model with the two classic ones and showing the proposed model’s dominancy, showing the helpful outcomes of collaborating 3PL with the SMEs in a cluster, proposing a “linear relaxation-based heuristic” procedure to yield a feasible initial solution within a significant shorter computational time and minimizing total supply chain costs of such IC by optimum application of facilities, lands and labor.

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Multi-level two-way cross-chain inventory coordination model that combines the same level with different levels in multi-supply chains

Cited by 2 publications

References 15 publications

Relocation of the distribution center of a motor oil producer reducing its storage capacity: A case study

Relocation of the distribution center of a motor oil producer reducing its storage capacity: A case study

A practical supply-demand hub in industrial clusters: a new perspective

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