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Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

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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 2022) | Viewed by 26262

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Special Issue Editors

Prof. Dr. Zsolt Tibor Kosztyán

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Guest Editor

Department of Quantitative Methods, Institute of Management, Faculty of Business and Economics, University of Pannonia, 8200 Veszprém, Hungary
Interests: operational research; project management; quantitative methods
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Zoltán Kovács

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Guest Editor

Department of Supply Chain Management, Institute of Management, Faculty of Business and Economics, University of Pannonia, 8200 Veszprém, Hungary
Interests: operational research; supply chain; logistics; simulations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the fore. Nevertheless, the recent pandemic situation, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects.

There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the epidemic situation has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects.

The aim of this Special Issue is to gather novel, original publications that offer new methods and approaches in the field of planning and scheduling in logistics and project planning that are able to respond to the challenges of the changing environment.

Prof. Dr. Zsolt Tibor Kosztyán
Prof. Dr. Zoltán Kovács
Guest Editors

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Keywords

resilience and flexibility in planning and scheduling
multi-objective decision making
risk evaluation and analysis
control and coordination in supply chains and networks
mathematical methods
operations research

Published Papers (13 papers)

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Editorial

Jump to: Research

3 pages, 191 KiB

Open AccessEditorial

Preface to the Special Issue on “Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling”

by Zsolt Tibor Kosztyán and Zoltán Kovács

Mathematics 2023, 11(1), 232; https://0-doi-org.brum.beds.ac.uk/10.3390/math11010232 - 03 Jan 2023

Cited by 1 | Viewed by 1273

Abstract

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the fore [...] Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

Research

Jump to: Editorial

27 pages, 2186 KiB

Open AccessArticle

A Flexible Robust Possibilistic Programming Approach toward Wood Pellets Supply Chain Network Design

by Zaher Abusaq, Muhammad Salman Habib, Adeel Shehzad, Mohammad Kanan and Ramiz Assaf

Mathematics 2022, 10(19), 3657; https://0-doi-org.brum.beds.ac.uk/10.3390/math10193657 - 06 Oct 2022

Cited by 13 | Viewed by 1649

Abstract

Increasing energy demand and the detrimental environmental impacts of fossil fuels have led to the development of renewable energy sources. Rapid demand growth for wood pellets over the last decade has established wood pellets as a potential renewable energy source in a globally competitive energy market. Integrated decision making including all stakeholders in the wood pellet supply chain (WPSC) is essential for a smooth transition to commercially viable wood pellet production. In this aspect, this study aims to suggest a decision support system for optimizing biomass-based wood pellet production supply chain network design (WPP-SCND). The WPP-SCND decision system minimizes the total supply chain (SC) cost of the system while also reducing carbon emissions associated with wood pellet SC activities. All objective parameters, including biomass availability at the supply terminals, market demand, and biomass production, are considered fuzzy to account for epistemic uncertainty. A fuzzy flexible robust possibilistic programming (fuzzy-FRPP) technique is developed for solving the suggested uncertain WPP-SCND model. The case findings show that the imprecise nature of the parameters has a significant impact on the strategic and tactical decisions in the wood pellet SC. By investing almost 10% of the total cost, robust decisions within the wood pellet SC can be obtained. It is established that the fuzzy-FRPP technique successfully provides robust decisions and achieves a balance between transportation costs, emissions costs, and economies of scale when making capacity decisions. Although the suggested decision support system is used to manage the production and distribution of wood pellets, the insights and solution methodology may be extended to the production of other biofuels. The proposed research may be valuable to authorities involved in planning large-scale wood pellet-related production-distribution projects. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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24 pages, 789 KiB

Open AccessArticle

Multi-Trip Time-Dependent Vehicle Routing Problem with Split Delivery

by Jie Zhang, Yifan Zhu, Xiaobo Li, Mengjun Ming, Weiping Wang and Tao Wang

Mathematics 2022, 10(19), 3527; https://0-doi-org.brum.beds.ac.uk/10.3390/math10193527 - 27 Sep 2022

Cited by 6 | Viewed by 1451

Abstract

Motivated by some practical applications of post-disaster supply delivery, we study a multi-trip time-dependent vehicle routing problem with split delivery (MTTDVRP-SD) with an unmanned aerial vehicle (UAV). This is a variant of the VRP that allows the UAV to travel multiple times; the task nodes’ demands are splittable, and the information is time-dependent. We propose a mathematical formulation of the MTTDVRP-SD and analyze the pattern of the solution, including the delivery routing and delivery quantity. We developed an algorithm based on the simulation anneal (SA) framework. First, the initial solution is generated by an improved intelligent auction algorithm; then, the stochastic neighborhood of the delivery route is generated based on the SA algorithm. Based on this, the model is simplified to a mixed-integer linear programming model (MILP), and the CPLEX optimizer is used to solve for the delivery quantity. The proposed algorithm is compared with random–simulation anneal–CPLEX (R-SA-CPLEX), auction–genetic algorithm–CPLEX (A-GA-CPLEX), and auction–simulation anneal–CPLEX (A-SA) on 30 instances at three scales, and its effectiveness and efficiency are statistically verified. The proposed algorithm significantly differs from R-SA-CPLEX at a 99% confidence level and outperforms R-SA-CPLEX by about 30%. In the large-scale case, the computation time of the proposed algorithm is about 30 min shorter than that of A-SA. Compared to the A-GA-CPLEX algorithm, the performance and efficiency of the proposed algorithm are improved. Furthermore, compared to a model that does not allow split delivery, the objective function values of the solution of the MTTDVRP-SD model are reduced by 52.67%, 48.22%, and 34.11% for the three scaled instances, respectively. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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20 pages, 3105 KiB

Open AccessArticle

Multipurpose Aggregation in Risk Assessment

by Zoltán Kovács, Tibor Csizmadia, István Mihálcz and Zsolt T. Kosztyán

Mathematics 2022, 10(17), 3166; https://0-doi-org.brum.beds.ac.uk/10.3390/math10173166 - 02 Sep 2022

Cited by 3 | Viewed by 1560

Abstract

Risk-mitigation decisions in risk-management systems are usually based on complex risk indicators. Therefore, aggregation is an important step during risk assessment. Aggregation is important when determining the risk of components or the overall risk of different areas or organizational levels. In this article, the authors identify different aggregation scenarios. They summarize the requirements of aggregation functions and characterize different aggregations according to these requirements. They critique the multiplication-based risk priority number (RPN) used in existing applications and propose the use of other functions in different aggregation scenarios. The behavior of certain aggregation functions in warning systems is also examined. The authors find that, depending on the aggregation location within the organization and the purpose of the aggregation, considerably more functions can be used to develop complex risk indicators. The authors use different aggregations and seriation and biclustering to develop a method for generating corrective and preventive actions. The paper provides contributions for individuals, organizations, and or policy makers to assess and mitigate the risks at all levels of the enterprise. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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15 pages, 304 KiB

Open AccessArticle

Scheduling with Resource Allocation, Deteriorating Effect and Group Technology to Minimize Total Completion Time

by Jia-Xuan Yan, Na Ren, Hong-Bin Bei, Han Bao and Ji-Bo Wang

Mathematics 2022, 10(16), 2983; https://0-doi-org.brum.beds.ac.uk/10.3390/math10162983 - 18 Aug 2022

Cited by 8 | Viewed by 1007

Abstract

This paper studies a single-machine problem with resource allocation (

R A

) and deteriorating effect (

D E

). Under group technology (

G T

) and limited resource availability, our goal is to determine the schedules of groups and jobs within [...] Read more.

This paper studies a single-machine problem with resource allocation (

R A

) and deteriorating effect (

D E

). Under group technology (

G T

) and limited resource availability, our goal is to determine the schedules of groups and jobs within each group such that the total completion time is minimized. For three special cases, polynomial time algorithms are given. For a general case, a heuristic, a tabu search algorithm, and an exact (i.e., branch-and-bound) algorithm are proposed to solve this problem. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

19 pages, 8733 KiB

Open AccessArticle

A Path Planning Model for Stock Inventory Using a Drone

by László Radácsi, Miklós Gubán, László Szabó and József Udvaros

Mathematics 2022, 10(16), 2899; https://0-doi-org.brum.beds.ac.uk/10.3390/math10162899 - 12 Aug 2022

Cited by 11 | Viewed by 2135

Abstract

In this study, a model and solution are shown for controlling the inventory of a logistics warehouse in which neither satellite positioning nor IoT solutions can be used. Following a review of the literature on path planning, a model is put forward using a drone that can be moved in all directions and is suitable for imaging and transmission. The proposed model involves three steps. In the first step, a traversal path definition provides an optimal solution, which is pre-processing. This is in line with the structure and capabilities of the warehouse. In the second step, the pre-processed path determines the real-time movement of the drone during processing, including camera movements and image capture. The third step is post-processing, i.e., the processing of images for QR code identification, the interpretation of the QR code, and the examination of matches and discrepancies for inventory control. A key benefit for the users of this model is that the result can be achieved without any external orientation tools, relying solely on its own movement and the organization of a pre-planned route. The proposed model can be effective not only for inventory control, but also for exploring the structure of a warehouse shelving system and determining empty cells. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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38 pages, 1451 KiB

Open AccessArticle

An Artificial Bee Colony Algorithm for Static and Dynamic Capacitated Arc Routing Problems

by Zsuzsanna Nagy, Ágnes Werner-Stark and Tibor Dulai

Mathematics 2022, 10(13), 2205; https://0-doi-org.brum.beds.ac.uk/10.3390/math10132205 - 24 Jun 2022

Cited by 6 | Viewed by 1481

Abstract

The Capacitated Arc Routing Problem (CARP) is a combinatorial optimization problem, which requires the identification of such route plans on a given graph to a number of vehicles that generates the least total cost. The Dynamic CARP (DCARP) is a variation of the CARP that considers dynamic changes in the problem. The Artificial Bee Colony (ABC) algorithm is an evolutionary optimization algorithm that was proven to be able to provide better performance than many other evolutionary algorithms, but it was not used for the CARP before. For this reason, in this study, an ABC algorithm for the CARP (CARP-ABC) was developed along with a new move operator for the CARP, the sub-route plan operator. The CARP-ABC algorithm was tested both as a CARP and a DCARP solver, then its performance was compared with other existing algorithms. The results showed that it excels in finding a relatively good quality solution in a short amount of time, which makes it a competitive solution. The efficiency of the sub-route plan operator was also tested and the results showed that it is more likely to find better solutions than other operators. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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20 pages, 1812 KiB

Open AccessArticle

Reconfiguration of Foodbank Network Logistics to Cope with a Sudden Disaster

by Esteban Ogazón, Neale R. Smith and Angel Ruiz

Mathematics 2022, 10(9), 1420; https://0-doi-org.brum.beds.ac.uk/10.3390/math10091420 - 23 Apr 2022

Cited by 3 | Viewed by 1814

Abstract

Foodbank networks provide adequate infrastructure and perform logistics activities to supply food to people in need on a day-to-day basis. However, in the case of a sudden event, such as a natural disaster, they must reconfigure themselves to quickly and fairly satisfy the needs of the affected people, despite the rapid changes in supply and demand, as much as possible. In contrast to most of the studies in the humanitarian logistics literature, which have focused on aid distribution—the downstream part of the supply chain—this paper extends the field of view upstream, explicitly considering supply (or, in the case of foodbanks, donors). To this end, we compare several network design strategies in order to assess the potential benefits of centralized decisions in a context where, in practice, there exists no formal protocol to support bank coordination. We propose a mathematical formulation for the design of such logistics processes, including collection, transshipment, and aid distribution, over a network of foodbanks inspired by the real case of Bancos de Alimentos de México (BAMX). The case considers several categories of food and encompasses restrictions on their mixture to ensure the nutritional quality of the delivered food, distinct from other models in the literature. Finally, we assess the differences in the strategies through the use of effectiveness and efficiency performance metrics. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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27 pages, 3482 KiB

Open AccessArticle

Mathematical Modelling of Inventory and Process Outsourcing for Optimization of Supply Chain Management

by Mohammed Alkahtani

Mathematics 2022, 10(7), 1142; https://0-doi-org.brum.beds.ac.uk/10.3390/math10071142 - 02 Apr 2022

Cited by 9 | Viewed by 3676

Abstract

Outsourcing is one of the major challenges for production firms in the current supply chain management (SCM) due to limited skilled workers and technology resources. There are too many parameters involved in the strategic decisions of the outsourcing level, quantity, quality, and cost. The outsourcing process removes the burden of capital investment; however, still it creates crucial concerns related to inventory control and production management by adding extra inventories. The semi-finished products are outsourced for a few processes due to limited resources and then returned to the manufacturer for the finishing operations. The article is based on the mathematical modeling and optimization of the process outsourcing considering imperfect production with variable quantity for the effective supply chain management. The numerical experiment was performed based on the data taken from the industry for the application of the proposed outsourcing-based SCM model. The results are significant in finding optimal production and outsourcing quantity with a minimum total cost of SCM. The sensitivity analysis was performed to see how important the effect of input parameters is on the total cost. The research is an important contribution in developing a mathematical model of process outsourcing in SCM. The research study is beneficial for managers to find the economic feasibility of process outsourcing for managing inventory and supply chain between manufacturer and outsourcing vendor. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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19 pages, 5184 KiB

Open AccessArticle

Analysis and Consequences on Some Aggregation Functions of PRISM (Partial Risk Map) Risk Assessment Method

by Ferenc Bognár and Csaba Hegedűs

Mathematics 2022, 10(5), 676; https://0-doi-org.brum.beds.ac.uk/10.3390/math10050676 - 22 Feb 2022

Cited by 14 | Viewed by 1681

Abstract

The PRISM (partial risk map) methodology is a novel risk assessment method developed as the combination of the failure mode and effect analysis and risk matrix risk assessment methods. Based on the concept of partial risks, three different aggregation functions are presented for assessing incident risks. Since the different aggregation functions give different properties to the obtained PRISM numbers and threshold surfaces (convex, concave, linear), the description of these properties is carried out. Similarity analyses based on the sum of ranking differences (SRD) method and rank correlation are performed and robustness tests are applied related to the changes of the assessment scale lengths. The PRISM method provides a solution for the systematically criticized problem of the FMEA, i.e., it is not able to deal with hidden risks behind the aggregated RPN number, while the method results in an expressive tool for risk management. Applying new aggregation functions, proactive assessment can be executed, and predictions can be given related to the incidents based on the nature of their hidden risk. The method can be suggested for safety science environments where human safety, environmental protection, sustainable production, etc., are highly required. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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23 pages, 1204 KiB

Open AccessArticle

An Inventory Model for Non-Instantaneously Deteriorating Items with Nonlinear Stock-Dependent Demand, Hybrid Payment Scheme and Partially Backlogged Shortages

by Md Al-Amin Khan, Ali Akbar Shaikh, Leopoldo Eduardo Cárdenas-Barrón, Abu Hashan Md Mashud, Gerardo Treviño-Garza and Armando Céspedes-Mota

Mathematics 2022, 10(3), 434; https://0-doi-org.brum.beds.ac.uk/10.3390/math10030434 - 29 Jan 2022

Cited by 15 | Viewed by 2711

Abstract

This research work presents an inventory model that involves non-instantaneous deterioration, nonlinear stock-dependent demand, and partially backlogged shortages by considering the length of the waiting time under a hybrid prepayment and cash-on-delivery scheme. The corresponding inventory problem is formulated as a nonlinear constraint optimization problem. The theoretical results for the unique optimal solution are presented, and eight special cases are also identified. Moreover, a salient theoretical result is provided: a certain condition where the optimal inventory policy may or may not involve deterioration. Finally, two numerical examples are provided using a sensitivity analysis to show the validity range of the inventory parameters. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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13 pages, 2690 KiB

Open AccessArticle

A Rich Vehicle Routing Problem for a City Logistics Problem

by Daniela Ambrosino and Carmine Cerrone

Mathematics 2022, 10(2), 191; https://0-doi-org.brum.beds.ac.uk/10.3390/math10020191 - 08 Jan 2022

Cited by 3 | Viewed by 1778

Abstract

In this work, a Rich Vehicle Routing Problem (RVRP) is faced for solving city logistic problems. In particular, we deal with the problem of a logistic company that has to define the best distribution strategy for obtaining an efficient usage of vehicles and for reducing transportation costs while serving customers with different priority demands during a given planning horizon. Thus, we deal with a multi-period vehicle routing problem with a heterogeneous fleet of vehicles, with customers’ requirements and company restrictions to satisfy, in which the fleet composition has to be daily defined. In fact, the company has a fleet of owned vehicles and the possibility to select, day by day, a certain number of vehicles from the fleet of a third-party company. Routing costs must be minimized together with the number of vehicles used. A mixed integer programming model is proposed, and an experimental campaign is presented for validating it. Tests have been used for evaluating the quality of the solutions in terms of both model behavior and service level to grant to the customers. Moreover, the benefits that can be obtained by postponing deliveries are evaluated. Results are discussed, and some conclusions are highlighted, including the possibility of formulating this problem in such a way as to use the general solver proposed in the recent literature. This seems to be the most interesting challenge to permit companies to improve the distribution activities. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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21 pages, 754 KiB

Open AccessArticle

A Districting Application with a Quality of Service Objective

by Eduardo Álvarez-Miranda and Jordi Pereira

Mathematics 2022, 10(1), 13; https://0-doi-org.brum.beds.ac.uk/10.3390/math10010013 - 21 Dec 2021

Cited by 2 | Viewed by 2172

Abstract

E-commerce sales have led to a considerable increase in the demand for last-mile delivery companies, revealing several problems in their logistics processes. Among these problems, are not meeting delivery deadlines. For example, in Chile, the national consumer service (SERNAC) indicated that in 2018, late deliveries represented 23% of complaints in retail online sales and were the second most common reason for complaints. Some of the causes are incorrectly designed delivery zones because in many cases, these delivery zones do not account for the demographic growth of cities. The result is an imbalanced workload between different zones, which leads to some resources being idle while others fail to meet their workload in satisfactory conditions. The present work proposes a hybrid method for designing delivery zones with an objective based on improving the quality of express delivery services. The proposed method combines a preprocess based on the grouping of demand in areas according to the structure of the territory, a heuristic that generates multiple candidates for the distribution zones, and a mathematical model that combines the different distribution zones generated to obtain a final territorial design. To verify the applicability of the proposed method, a case study is considered based on the real situation of a Chilean courier company with low service fulfillment in its express deliveries. The results obtained from the computational experiments show the applicability of the method, highlighting the validity of the aggregation procedure and improvements in the results obtained using the hybrid method compared to the initial heuristic. The final solution improves the ability to meet the conditions associated with express deliveries, compared with the current situation, by 12 percentage points. The results also allow an indicative sample of the critical service factors of a company to be obtained, identifying the effects of possible changes in demand or service conditions. Full article

(This article belongs to the Special Issue Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling)

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