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Information
Special Issues
Modeling of Supply Chain Systems
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Modeling of Supply Chain Systems

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 17236

Special Issue Editor

Dr. Zina Ben Miled

E-Mail Website
Guest Editor
Electrical and Computer Engineering Department, School of Engineering and Technology, Indiana University Purdue University at Indianapolis, Indianapolis, IN 46205, USA
Interests: machine learning; data analytics; complex systems modeling

Special Issue Information

Dear Colleagues,

The increasing complexity and interdependence of supply chain systems, processes acting on these systems, and the networks facilitating the flow of goods and information between supply chain systems call for innovative technologies and methodologies that can efficiently support planning and operation throughout the various phases of the product life cycle. Supply chain systems involve multiple stakeholders with widely varying cooperative and competitive interests. This Special Issue calls for papers that describe new modeling methodologies and case studies that demonstrate how these methodologies can improve the efficiency and resilience of supply chain systems.

Predictive and analytical models that address the challenges and supply chain vulnerabilities of the various phases of the product life cycle are encouraged. Models that focus on the impact of infrastructures and the environment on supply chain processes or on supply chain disruptive events are welcome.

Interested authors are invited to contribute their original, unpublished work. Topics of interest include but are not limited to:

  • Predictive models for supply chain processes;
  • Analytical models for planning and operation decision support;
  • Complex adaptive supply chain systems;
  • Modeling of collaborative, cooperative and/or competitive systems;
  • Distributed system modeling;
  • Case studies and applications of new technologies;
  • Contributed data and data repositories.

Dr. Zina Ben Miled
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Editorial

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3 pages, 669 KiB  
Editorial
Special Issue “Modeling of Supply Chain Systems”
by Zina Ben Miled
Information 2020, 11(11), 494; https://0-doi-org.brum.beds.ac.uk/10.3390/info11110494 - 22 Oct 2020
Viewed by 1309
Abstract
Supply chain systems are complex networks of producers, service providers and consumers [...] Full article
(This article belongs to the Special Issue Modeling of Supply Chain Systems)

Research

Jump to: Editorial

24 pages, 3137 KiB  
Article
Proposing a Supply Chain Collaboration Framework for Synchronous Flow Implementation in the Automotive Industry: A Moroccan Case Study
by Imane Ibn El Farouk, Imane Moufad, Youness Frichi, Jabir Arif and Fouad Jawab
Information 2020, 11(9), 431; https://0-doi-org.brum.beds.ac.uk/10.3390/info11090431 - 07 Sep 2020
Cited by 16 | Viewed by 5530
Abstract
The present paper reports on studying synchronous flow implementation, as a lean supply chain tools, through a collaborative relationship with suppliers. This involves consolidating with a new contribution to the development and application of a supply chain collaboration framework between automotive constructor and [...] Read more.
The present paper reports on studying synchronous flow implementation, as a lean supply chain tools, through a collaborative relationship with suppliers. This involves consolidating with a new contribution to the development and application of a supply chain collaboration framework between automotive constructor and first-tier equipment suppliers to achieve the synchronous flow of components. The objective is to provide the automotive companies with a decision-making tool for selecting strategic suppliers to collaborate with, examining the collaboration context in terms of motivators, drivers, and barriers and evaluating the collaboration performance. Therefore, our contribution is structured as follows. As a first step, an overview of papers reporting on collaboration, lean supply chain, and synchronous flow is provided to identify the key elements of successful collaboration relationships. As a result, a preliminary framework is elaborated. The second step described the case study of a leading automotive firm “RENAULT” and its suppliers in Morocco. Based on semi-structured interviews conducted with participants from these companies, the preliminary framework was improved. The next section discusses the obtained results as well as the improved framework. Finally, conclusions and suggestions for further works are included. Full article
(This article belongs to the Special Issue Modeling of Supply Chain Systems)
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17 pages, 1642 KiB  
Article
Risk Assessment Framework for Outbound Supply-Chain Management
by Mark Krystofik, Christopher J. Valant, Jeremy Archbold, Preston Bruessow and Nenad G. Nenadic
Information 2020, 11(9), 417; https://0-doi-org.brum.beds.ac.uk/10.3390/info11090417 - 28 Aug 2020
Cited by 5 | Viewed by 3745
Abstract
We developed a framework for the risk assessment of delaying the delivery of shipments to customers in the presence of incomplete information pertaining to a significant, e.g., weather-related, event that could cause substantial disruption. The approach was anchored in existing manual practices, but [...] Read more.
We developed a framework for the risk assessment of delaying the delivery of shipments to customers in the presence of incomplete information pertaining to a significant, e.g., weather-related, event that could cause substantial disruption. The approach was anchored in existing manual practices, but equipped with a mechanism for collecting critical data and incorporating it into decision-making, paving the path to gradual automation. Two key variables that affect the risk were: the likelihood of an event and the importance of the specific shipment. User-specified event likelihood, with elliptical spatial component, allowed the model to attach different probabilistic interpretations; uniform and Gaussian probability distributions were discussed, including possible paths for extensions. The framework development included a practical implementation in the Python scientific ecosystem. Although the framework was demonstrated in a prototype environment, the results clearly showed that the framework was quickly able to show scheduled and in-process shipments that were at risk of delay, while also providing a prioritized ranking of these shipments in order for personnel within the manufacturing organization to quickly implement mitigation actions and proactive communications with customers to ensure critical shipments were delivered when needed. Since the framework pulled in data from various business information systems, the framework proved to assist personnel to quickly identify potentially impacted shipments much faster than existing methods, which resulted in improved efficiency and customer satisfaction. Full article
(This article belongs to the Special Issue Modeling of Supply Chain Systems)
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23 pages, 2227 KiB  
Article
The Effect of Limited Resources in the Dynamic Vehicle Routing Problem with Mixed Backhauls
by Georgios Ninikas and Ioannis Minis
Information 2020, 11(9), 414; https://0-doi-org.brum.beds.ac.uk/10.3390/info11090414 - 27 Aug 2020
Cited by 3 | Viewed by 2115
Abstract
In the dynamic vehicle routing problem with mixed backhauls (DVRPMB) both pick up orders and delivery orders, not related to each other, are served. The requests of the former arrive dynamically while the latter are known a priori. In this study, we focus [...] Read more.
In the dynamic vehicle routing problem with mixed backhauls (DVRPMB) both pick up orders and delivery orders, not related to each other, are served. The requests of the former arrive dynamically while the latter are known a priori. In this study, we focus on the case of limited fleet, which fulfills all delivery orders, but may not have enough capacity to serve all pick up orders within the available working horizon. The problem’s dynamic nature and the attention to customer service raise interesting considerations, especially related to the problem’s objectives. The problem is solved through periodic re-optimization, acknowledging the fact that this pseudo-dynamic approach may lead to some limitations. For the underlying (static) optimization problem we propose appropriate objective functions, which account for vehicle productivity and propose a branch-and-price (BP) approach to solve it to optimality. The results indicate how the performance of the various objectives is impacted by different re-optimization frequencies and policies in this practically relevant environment of dynamic demand served by a limited fleet. Specifically, extensive experimentation indicates that accounting for vehicle productivity within a typical periodic re-optimization solution framework may result to higher customer service under a range of operational settings, in comparison to conventional objectives. Full article
(This article belongs to the Special Issue Modeling of Supply Chain Systems)
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21 pages, 3177 KiB  
Article
Model for Collaboration among Carriers to Reduce Empty Container Truck Trips
by Majbah Uddin and Nathan Huynh
Information 2020, 11(8), 377; https://0-doi-org.brum.beds.ac.uk/10.3390/info11080377 - 26 Jul 2020
Cited by 6 | Viewed by 4001
Abstract
In recent years, intermodal transport has become an increasingly attractive alternative to freight shippers. However, the current intermodal freight transport is not as efficient as it could be. Oftentimes an empty container needs to be transported from the empty container depot to the [...] Read more.
In recent years, intermodal transport has become an increasingly attractive alternative to freight shippers. However, the current intermodal freight transport is not as efficient as it could be. Oftentimes an empty container needs to be transported from the empty container depot to the shipper, and conversely, an empty container needs to be transported from the receiver to the empty container depot. These empty container movements decrease the freight carrier’s profit, as well as increase traffic congestion, decrease roadway safety, and add unnecessary emissions to the environment. To this end, our study evaluates a potential collaboration strategy to be used by carriers for domestic intermodal freight transport based on an optimization approach to reduce the number of empty container trips. A binary integer-linear programming model is developed to determine each freight carrier’s optimal schedule while minimizing its operating cost. The model ensures that the cost for each carrier with collaboration is less than or equal to its cost without collaboration. It also ensures that average savings from the collaboration are shared equally among all participating carriers. Additionally, two stochastic models are provided to account for uncertainty in truck travel times. The proposed collaboration strategy is tested using empirical data and is demonstrated to be effective in meeting all of the shipment constraints. Full article
(This article belongs to the Special Issue Modeling of Supply Chain Systems)
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