Submit to Special Issue Submit Abstract to Special Issue Review for Axioms Edit a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Special Issue "Applied Mathematical Modeling and Optimization"

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 20 September 2023 | Viewed by 4449

Share This Special Issue

Special Issue Editor

Prof. Dr. Abraham Mendoza

E-Mail Website
Guest Editor

Facultad de Ingeniería, Universidad Panamericana, Zapopan 45019, JA, Mexico
Interests: supply chain logistics; operations management; transportation and facility design; material handling

Special Issue Information

Dear Colleagues,

This Special Issue focuses on current advances in “Applied Mathematical Modeling and Optimization” and includes novel research on modeling and optimization of engineering, manufacturing, and industrial systems problems using deterministic methods, evolutionary algorithms, and new optimization methods and algorithms. Contributions focusing on novel mathematical modeling, applications, or both are encouraged.

Potential topics include but are not limited to:

Mathematical modeling;
Novel models of engineering problems;
Numerical optimization;
Evolutionary algorithms;
New optimization methods;
Supply chain modeling and optimization;
Mathematical modeling and optimization of engineering problems;
Modeling and optimization of electrical and electronic systems.

Prof. Dr. Abraham Mendoza
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. Axioms 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.

Keywords

mathematical modeling
optimization
Heuristics
supply chain optimization
system optimization

Published Papers (6 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Open AccessArticle

A Mathematical Model for an Inventory Management and Order Quantity Allocation Problem with Nonlinear Quantity Discounts and Nonlinear Price-Dependent Demand

Avelina Alejo-Reyes

Abraham Mendoza

Erik Cuevas

and

Miguel Alcaraz-Rivera

Axioms 2023, 12(6), 547; https://doi.org/10.3390/axioms12060547 - 01 Jun 2023

Viewed by 156

Abstract

This article focuses on solving the order quantity allocation problem for retailers. It considers factors such as quality constraints, nonlinear quantity discounts, and price-dependent demand. By formulating it as a nonlinear maximization problem, the article aims to find the best combination of suppliers and order quantity out of infinite solutions to maximize the retailer’s profit. The main contribution of this research is a new mathematical model that can solve the problem of quality constraint and demand in a single step. This problem is complex due to the number of equations, their nonlinear nature, and the various trade-offs given by the market. Additionally, this research considers demand as output and includes price-dependent demand, which is more realistic for retailers. The proposed model was tested using an example from the recent literature and showed better results than the previously published best solution regarding profit maximization. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Figure 1

Open AccessArticle

A Modified Simulated Annealing (MSA) Algorithm to Solve the Supplier Selection and Order Quantity Allocation Problem with Non-Linear Freight Rates

Paulina Gonzalez-Ayala

Avelina Alejo-Reyes

Erik Cuevas

and

Abraham Mendoza

Axioms 2023, 12(5), 459; https://doi.org/10.3390/axioms12050459 - 09 May 2023

Viewed by 543

Abstract

Economic Order Quantity (EOQ) is an important optimization problem for inventory management with an impact on various industries; however, their mathematical models may be complex with non-convex, non-linear, and non-differentiable objective functions. Metaheuristic algorithms have emerged as powerful tools for solving complex optimization problems (including EOQ). They are iterative search techniques that can efficiently explore large solution spaces and obtain near-optimal solutions. Simulated Annealing (SA) is a widely used metaheuristic method able to avoid local suboptimal solutions. The traditional SA algorithm is based on a single agent, which may result in a low convergence rate for complex problems. This article proposes a modified multiple-agent (population-based) adaptive SA algorithm; the adaptive algorithm imposes a slight attraction of all agents to the current best solution. As a proof of concept, the proposed algorithm was tested on a particular EOQ problem (recently studied in the literature and interesting by itself) in which the objective function is non-linear, non-convex, and non-differentiable. With these new mechanisms, the algorithm allows for the exploration of different regions of the solution space and determines the global optimum in a faster manner. The analysis showed that the proposed algorithm performed well in finding good solutions in a reasonably short amount of time. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Figure 1

Open AccessArticle

Efficiency of Orthogonal Matching Pursuit for Group Sparse Recovery

and

Axioms 2023, 12(4), 389; https://doi.org/10.3390/axioms12040389 - 17 Apr 2023

Viewed by 417

Abstract

We propose the Group Orthogonal Matching Pursuit (GOMP) algorithm to recover group sparse signals from noisy measurements. Under the group restricted isometry property (GRIP), we prove the instance optimality of the GOMP algorithm for any decomposable approximation norm. Meanwhile, we show the robustness [...] Read more.

γ

-decomposability is not required. The simulation results show that the GOMP is very efficient for group sparse signal recovery and significantly outperforms Basis Pursuit in both scalability and solution quality. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Figure 1

Open AccessArticle

Mathematical Model to Calculate Heat Transfer in Cylindrical Vessels with Temperature-Dependent Materials

Martina Fernández-Gracía

Juan Francisco Sánchez-Pérez

Francisco del Cerro

and

Manuel Conesa

Axioms 2023, 12(4), 335; https://doi.org/10.3390/axioms12040335 - 29 Mar 2023

Viewed by 536

Abstract

In this article, a mathematical model capable of simulating the heat transfer of cylindrical vessels whose properties are dependent on temperature is proposed. As a case study, it compares, from an approach of their heat transfer and chemical migration characteristics as a function of the temperature reached, different materials commonly used for the manufacture of water bottles. More specifically, the materials studied were aluminium, polyethylene terephthalate, and polypropylene. The validation of the model consists of an experiment carried out in the laboratory with three water bottles of each of the materials under study, as well as simulations using the Network Simulation Method to recreate the heat transfer that occurs through the walls of the bottles. On the other hand, the nondimensionalization technique is also applied, which allows us to obtain the weight of each of the variables on the problem, as well as the existing relationship between them. Finally, an outside temperature of 30 °C to 50 °C is simulated, which is a common temperature range in southern Europe during the summer season, and an initial temperature of 20 °C for the water contained in the bottle to know the behaviour of the materials and what the final temperature of the water would be after one hour. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Figure 1

Open AccessArticle

Incentive Contracts for a Queueing System with a Strategic Server: A Principal-Agent Perspective

Jun Tu

Xiaoying Hu

and

Min Huang

Axioms 2023, 12(3), 272; https://doi.org/10.3390/axioms12030272 - 06 Mar 2023

Viewed by 774

Abstract

Queueing systems with strategic servers are common in the service industry. The self-interested service rate decision of the strategic server will be detrimental to the queueing system. To improve the service rates, designing incentive contracts for the server from the queueing system owner’s perspective is critical. This study investigates the incentive contracts of queueing systems under exogenous and endogenous price scenarios. The unit-price and cost-sharing contracts are introduced to coordinate the queueing system. The effects of pricing mechanisms and contract types on the queueing system are investigated theoretically and experimentally. The results reveal that regardless of whether the price scenario is exogenous or endogenous, the cost-sharing contract is more effective than the unit-price contract in incentivizing the server to make a service effort. The cost-sharing contract with endogenous price can reduce the service price. The cost-sharing contract can boost profits for both the owner and server, albeit with conditions. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Figure 1

Open AccessArticle

Robot Time-Optimal Trajectory Planning Based on Quintic Polynomial Interpolation and Improved Harris Hawks Algorithm

Jing Xu

Chaofan Ren

and

Xiaonan Chang

Axioms 2023, 12(3), 245; https://doi.org/10.3390/axioms12030245 - 27 Feb 2023

Viewed by 1084

Abstract

Time-optimal trajectory planning is one of the most important ways to improve work efficiency and reduce cost and plays an important role in practical application scenarios of robots. Therefore, it is necessary to optimize the running time of the trajectory. In this paper, a robot time-optimal trajectory planning method based on quintic polynomial interpolation and an improved Harris hawks algorithm is proposed. Interpolation with a quintic polynomial has a smooth angular velocity and no acceleration jumps. It has widespread application in the realm of robot trajectory planning. However, the interpolation time is usually obtained by testing experience, and there is no unified criterion to determine it, so it is difficult to obtain the optimal trajectory running time. Because the Harris hawks algorithm adopts a multi-population search strategy, compared with other swarm intelligent optimization algorithms such as the particle swarm optimization algorithm and the fruit fly optimization algorithm, it can avoid problems such as single population diversity, low mutation probability, and easily falling into the local optimum. Therefore, the Harris hawks algorithm is introduced to overcome this problem. However, because some key parameters in HHO are simply set to constant or linear attenuation, efficient optimization cannot be achieved. Therefore, the nonlinear energy decrement strategy is introduced in the basic Harris hawks algorithm to improve the convergence speed and accuracy. The results show that the optimal time of the proposed algorithm is reduced by 1.1062 s, 0.5705 s, and 0.3133 s, respectively, and improved by 33.39%, 19.66%, and 12.24% compared with those based on particle swarm optimization, fruit fly algorithm, and Harris hawks algorithms, respectively. In multiple groups of repeated experiments, compared with particle swarm optimization, the fruit fly algorithm, and the Harris hawks algorithm, the computational efficiency was reduced by 4.7019 s, 1.2016 s, and 0.2875 s, respectively, and increased by 52.40%, 21.96%, and 6.30%. Under the optimal time, the maximum angular displacement, angular velocity, and angular acceleration of each joint trajectory meet the constraint conditions, and their average values are only 75.51%, 38.41%, and 28.73% of the maximum constraint. Finally, the robot end-effector trajectory passes through the pose points steadily and continuously under the cartesian space optimal time. Full article

(This article belongs to the Special Issue Applied Mathematical Modeling and Optimization)

► Show Figures

Journal Menu

Journal Browser

Special Issue "Applied Mathematical Modeling and Optimization"

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (6 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI