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Mathematics
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Application of Mathematical Modeling in Operations Research
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Application of Mathematical Modeling in Operations Research

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 November 2023) | Viewed by 2181

Special Issue Editor

Dr. Baruch Mor

E-Mail Website
Guest Editor
Department of Economics and Business Administration, Ariel University, Ariel 40700, Israel
Interests: algorithms in multi-agent scheduling

Special Issue Information

Dear colleague,

Scheduling theory is a fundamental branch of operations research (OR). Many concepts of computer science (CS) are used extensively in OR, including computational complexity, NP-hardness, dynamic programing (DP), and fixed-parameter tractable (FPT) algorithms. Several well-known scheduling algorithms are considered unfeasible, mainly due to the NP-hardness nature of the underlying problems. A common approach to coping with suboptimal solutions suggests using fully polynomial-time approximation schemes (FPTAS) or metaheuristics (e.g., simulated annealing, genetic algorithms), achieving faster running times while compromising on an optimal result.

Dr. Baruch Mor
Guest Editor

Manuscript Submission Information

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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

  • deterministic scheduling theory
  • linear programming
  • nonlinear programming
  • discrete optimization
  • combinatorial optimization
  • dynamic programming
  • heuristics

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Published Papers (2 papers)

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Research

16 pages, 6070 KiB  
Article
Optimizing Mixed Group Train Operation for Heavy-Haul Railway Transportation: A Case Study in China
by Qinyu Zhuo, Weiya Chen and Ziyue Yuan
Mathematics 2023, 11(23), 4712; https://doi.org/10.3390/math11234712 - 21 Nov 2023
Viewed by 898
Abstract
Group train operation (GTO) applications have reduced the tracking intervals for overloaded trains, and can affect the efficiency of rail transport. In this paper, we first analyze the differences between GTO and traditional operation (TO). A new mathematical model and simulated annealing algorithm [...] Read more.
Group train operation (GTO) applications have reduced the tracking intervals for overloaded trains, and can affect the efficiency of rail transport. In this paper, we first analyze the differences between GTO and traditional operation (TO). A new mathematical model and simulated annealing algorithm are then used to study the problem of mixed group train operation. The optimization objective of this model is to maximize the transportation volume of special heavy-haul railway lines within the optimization period. The main constraint conditions are extracted from the maintenance time, the minimum ratio of freight volume, and the committed arrival time at each station. A simulated annealing algorithm is constructed to generate the mixed GTO plan. Through numerical experiments conducted on actual heavy-haul railway structures, we validate the effectiveness of the proposed model and meta-heuristic algorithm. The results of the first contrastive experiment show that the freight volume for group trains is 37.5% higher than that of traditional trains, and the second experiment shows a 30.6% reduction in the time during which the line is occupied by trains in GTO. These findings provide compelling evidence that GTO can effectively enhance the capacity and reduce the transportation time cost of special heavy-haul railway lines. Full article
(This article belongs to the Special Issue Application of Mathematical Modeling in Operations Research)
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17 pages, 2135 KiB  
Article
Optimal Fair-Workload Scheduling: A Case Study at Glorytek
by Tzu-Chin Lin and Bertrand M. T. Lin
Mathematics 2023, 11(19), 4051; https://doi.org/10.3390/math11194051 - 24 Sep 2023
Viewed by 1029
Abstract
Taichung is the center of the Taiwanese precision optical industry. Optics companies are modernized and automated, with most running 24 h production lines. With machines running around the clock, production lines must be assigned engineers to handle unexpected situations. The optical lens industry [...] Read more.
Taichung is the center of the Taiwanese precision optical industry. Optics companies are modernized and automated, with most running 24 h production lines. With machines running around the clock, production lines must be assigned engineers to handle unexpected situations. The optical lens industry depends on precision technology. For fully automated production lines, each production process requires an engineer to be on call to troubleshoot production problems in real-time. However, shifts are currently scheduled manually, and the staff of each unit are responsible for scheduling the various production processes for each month. Administrative staff for each engineering department must take half a day to one day to complete the shift for a month, with results that usually do not ensure the best average workload, often leading engineers to question its fairness. Considering the manpower requirements for the actual production line shift and the fairness of balancing shifts, the scope of this study is the shift scheduling of engineering staff in the assembly line to perform different duties during a fixed cycle. The research aims to provide a solution for Glorytek to increase the efficiency of engineering shift scheduling and optimize the allocation of engineering staff. We will compare the duty allocation and efficiency of the current manual shift scheduling system with a new automated one. The results show that the efficiency of shift scheduling arrangements increased by more than 96%, and the maximum number of days of staff attendance (5 days) is less than that for manual assignment (6 days) while still satisfying the shift limits stipulated by the company. Two factors remain when implementing the proposed system. First, due to technical concerns, the internal process of the scheduling arrangement would be shifted from administrative staff to the IT department. Another concern is the inevitable investment in off-the-shelf optimization software. Full article
(This article belongs to the Special Issue Application of Mathematical Modeling in Operations Research)
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