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Mathematical Methods and Operations Research in Planning, Scheduling and Supply...
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Mathematical Methods and Operations Research in Planning, Scheduling and Supply Chain

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 3771

Special Issue Editors

Dr. Christophe Sauvey

E-Mail Website
Guest Editor
Computer Engineering, Production and Maintenance Laboratory, Université de Lorraine, Metz, France
Interests: operations research; mathematical modelling; optimization; industrial engineering; electrical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Wajdi Trabelsi

E-Mail Website
Guest Editor
ICN Business School, LGIPM, F-57000 Metz, France
Interests: combinatorial optimization; heuristics and meta-heuristics design; scheduling and applications; mathematical modelling of coupled problems; logistics and production; optimization; supply chain management

Special Issue Information

Dear colleagues,

Mathematical methods and operation research tools have been useful over recent decades to solve many industrial problems, such as supply chain design, planning or scheduling issues. Through the development of new technologies, the industries of today are experiencing the fourth revolution, referred to as Industry 4.0, and are anticipating the fifth revolution, which will allow us to merge the power of smart, precise and accurate machinery with human creativity and ingenuity.

This reality has a significant impact on industrial management processes; as long as people are working alongside robots and smart machines, we will need active, efficient and agile tools to take advantage of the technologies and intelligence integrated throughout the supply chain.

This Special Issue aims to present recent advances in the following topics:

  • Scheduling optimization under multiple industrial constraints;
  • Supply chain operations management;
  • Production planning in a sustainable supply chain;
  • Planning optimization under uncertainties and human aims considerations;
  • Emergency/e-commerce/reverse/green/metropolitan/5.0 logistics;
  • Scheduling in sustainable manufacturing;
  • Optimal decisions, hybrid optimization and multi-objective optimization;
  • Sustainable logistics systems design;
  • Modelling and optimization of complex industrial processes;
  • Digital technologies support for logistics and supply chain management adaptation.

Dr. Christophe Sauvey
Dr. Wajdi Trabelsi
Guest Editors

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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.

Keywords

  • operations research
  • logistics management
  • supply chain management
  • planning under carbon footprint constraints
  • green manufacturing
  • Industry 5.0
  • mathematical methods
  • optimization
  • Internet of Things
  • population-based intelligent algorithms

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Published Papers (3 papers)

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Research

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20 pages, 372 KiB  
Article
Single-Machine Scheduling with Simultaneous Learning Effects and Delivery Times
by Zheng Liu and Ji-Bo Wang
Mathematics 2024, 12(16), 2522; https://doi.org/10.3390/math12162522 - 15 Aug 2024
Viewed by 746
Abstract
This paper studies the single-machine scheduling problem with truncated learning effect, time-dependent processing time, and past-sequence-dependent delivery time. The delivery time is the time that the job is delivered to the customer after processing is complete. The goal is to determine an optimal [...] Read more.
This paper studies the single-machine scheduling problem with truncated learning effect, time-dependent processing time, and past-sequence-dependent delivery time. The delivery time is the time that the job is delivered to the customer after processing is complete. The goal is to determine an optimal job schedule to minimize the total weighted completion time and maximum tardiness. In order to solve the general situation of the problem, we propose a branch-and-bound algorithm and other heuristic algorithms. Computational experiments also prove the effectiveness of the given algorithms. Full article
(This article belongs to the Special Issue Mathematical Methods and Operations Research in Planning, Scheduling and Supply Chain)
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14 pages, 1230 KiB  
Article
Commodity Pricing and Replenishment Decision Strategy Based on the Seasonal ARIMA Model
by Jiaying Liu and Bin Liu
Mathematics 2023, 11(24), 4921; https://doi.org/10.3390/math11244921 - 11 Dec 2023
Cited by 3 | Viewed by 1465
Abstract
As a crucial component of enterprise marketing strategy, commodity pricing and replenishment strategies often play a pivotal role in determining the profit of retailers. In pursuit of profit maximization, this work delved into the realm of fresh food supermarket commodity pricing and replenishment [...] Read more.
As a crucial component of enterprise marketing strategy, commodity pricing and replenishment strategies often play a pivotal role in determining the profit of retailers. In pursuit of profit maximization, this work delved into the realm of fresh food supermarket commodity pricing and replenishment strategies. We classified commodities into six distinct categories and proceeded to examine the relationship between the total quantity sold in these categories and cost-plus pricing through Pearson correlation analysis. Furthermore, a Seasonal ARIMA model was established for the prediction of replenishment quantities and pricing strategies for each of the categories over a seven-day period. To ensure precise data, we extended our forecasting to individual products for a single day, employing 0–1 integer programming. To align the inquiry with real-world scenarios, we took into account various factors, including refunds, waste, discounts, and the requirement that individual products fall within specific selling ranges. The results show that the profit will be maximized when the replenishment of chili is 39.874 kg and the replenishment of edible mushrooms is 43.257 kg in the future week. We assume that the residual of the model is white noise. By testing the white noise of the model, the analysis of the residual Q statistic results shows that it is not significant in level, which can prove that the model meets the requirements and the obtained results are reliable. This research provides valuable insights into the realm of commodity pricing and replenishment strategy, offering practical guidance for implementation. Full article
(This article belongs to the Special Issue Mathematical Methods and Operations Research in Planning, Scheduling and Supply Chain)
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Review

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31 pages, 1259 KiB  
Review
Multi-Objective Production Rescheduling: A Systematic Literature Review
by Sofia Holguin Jimenez, Wajdi Trabelsi and Christophe Sauvey
Mathematics 2024, 12(20), 3176; https://doi.org/10.3390/math12203176 - 11 Oct 2024
Viewed by 872
Abstract
Production rescheduling involves re-optimizing production schedules in response to disruptions that render the initial schedule inefficient or unfeasible. This process requires simultaneous consideration of multiple objectives to develop new schedules that are both efficient and stable. However, existing review papers have paid limited [...] Read more.
Production rescheduling involves re-optimizing production schedules in response to disruptions that render the initial schedule inefficient or unfeasible. This process requires simultaneous consideration of multiple objectives to develop new schedules that are both efficient and stable. However, existing review papers have paid limited attention to the multi-objective optimization techniques employed in this context. To address this gap, this paper presents a systematic literature review on multi-objective production rescheduling, examining diverse shop-floor environments. Adhering to the PRISMA guidelines, a total of 291 papers were identified. From this pool, studies meeting the inclusion criteria were selected and analyzed to provide a comprehensive overview of the problems tackled, dynamic events managed, objectives considered, and optimization approaches discussed in the literature. This review highlights the primary multi-objective optimization methods used in relation to rescheduling strategies and the dynamic disruptive events studied. Findings reveal a growing interest in this research area, with “a priori” and “a posteriori” optimization methods being the most commonly implemented and a notable rise in the use of the latter. Hybridized algorithms have shown superior performance compared to standalone algorithms by leveraging combined strengths and mitigating individual weaknesses. Additionally, “interactive” and “Pareto pruning” methods, as well as the consideration of human factors in flexible production systems, remain under-explored. Full article
(This article belongs to the Special Issue Mathematical Methods and Operations Research in Planning, Scheduling and Supply Chain)
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