A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System

Logistics · 2024-03-04 · 3 citations

Background: This study addresses optimising fleet size in a system with a heterogeneous truck fleet, aiming to minimise transportation costs in interfacility material transfer operations. Methods: The material transfer process is modelled using a closed queueing network (CQN) that considers heterogeneous nodes and customised service times tailored to the unique characteristics of various truck types and their transported materials. The optimisation problem is formulated as a mixed-integer nonlinear programming (MINLP), falling into the NP-Hard, making exact solution computation challenging. A numerical approximation method, a modified sequential quadratic programming (SQP) method coupled with a mean value analysis (MVA) algorithm, is employed to overcome this challenge. Validation is conducted using a discrete event simulation (DES) model. Results: The proposed analytical model tested within a steel manufacturing plant’s material transfer process. The results showed that the analytical model achieved comparable optimisation of the heterogeneous truck fleet size with significantly reduced response times compared to the simulation method. Furthermore, evaluating performance metrics, encompassing response time, utilisation rate, and cycle time, revealed minimal discrepancies between the analytical and the simulation results, approximately ±8%, ±8%, and ±7%, respectively. Conclusions: These findings affirm the presented analytical approach’s robustness in optimising interfacility material transfer operations with heterogeneous truck fleets, demonstrating real-world applications.

Queueing network models for the analysis and optimisation of material handling systems: a systematic literature review

Flexible Services and Manufacturing Journal · 2023-09-07 · 17 citations

Abstract Material handling systems (MHSs) are an integral part of logistics functions in manufacturing and service organizations. Material handling equipment (MHE) is considered the pivotal actor of any given MHS. Decisions ranging from the strategic level, such as selecting the proper MHE, capacity, and ownership (in-house or outsourcing) to operational level decisions such as resource allocation, scheduling, and routing of MHEs, are critical to the efficiency of an MHS. Industry practitioners use various methods and tools to evaluate these MHSs to find the best policies for their operations. This study identifies past works related to the performance evaluation and optimisation of MHSs using queueing network models. Moreover, this study provides a comprehensive analysis of identified research questions. The study methodology adopts a systematic literature review, bibliometric, and content analysis techniques proposed in similar research studies. This study provides material logistics scholars and practitioners with a thorough understanding of queueing networks as a modelling tool for analysing MHS applications in various domains.

Optimal Buffers Allocation in an Inter-facility Material Transfer System Modelled as a Closed Queueing Network and Analysed Through a Simulation-Optimisation Approach

2023-03-09

Queueing is a common phenomenon in manufacturing and service environments. Practitioners often use queueing network models to analyse these systems for decision-making processes. However, finite queueing systems with blocking are used to a lesser extent due to the complexity of solving the systems. Generally, closed queueing networks (CQN) with finite capacities do not lend themselves to product-form solutions and must be solved using approximation algorithms. This study considers the problem of determining the optimal buffers allocation for an inter-facility material transportation system in a manufacturing facility considering the blocking after service (BAS) phenomenon. Under BAS, a job can only reach the next node until there is space available in the queue of the next node. If the queue capacity of the destination node is full, the job in the preceding node, even after being serviced, will block that server. In a typical material flow, trucks transfer materials between the facility and undergo several sub-processes such as gate entry, weighing, loading, and unloading. This material flow process is modelled using a CQN, and each sub-process is designed as a node with a finite queueing capacity. An analytical model is developed within this context to determine the optimal buffer sizes to maximise the system's throughput. More specifically, a simulation model is developed using the Anylogic software, and the optimisation problem is incorporated into the model to determine the optimal buffer allocations. The Anylogic simulation-optimisation experiment engine uses various metaheuristics through the OptQuest tool to determine the non-dominated solutions of the corresponding CQN.

Optimisation of Buffer Allocations in Manufacturing Systems: A Study on Intra and Outbound Logistics Systems Using Finite Queueing Networks

Applied Sciences · 2023-08-23 · 17 citations

Optimal buffer allocations can significantly improve system throughput by managing variability and disruptions in manufacturing or service operations. Organisations can minimise waiting times and bottlenecks by strategically placing buffers along the flow path, leading to a smoother and more efficient production or service delivery process. Determining the optimal size of buffers poses a challenging dilemma, as it involves balancing the cost of buffer allocation, system throughput, and waiting times at each service station. This paper presents a framework that utilises finite queueing networks for performance analysis and optimisation of topologies, specifically focusing on buffer allocations. The proposed framework incorporates a finite closed queuing network to model the intra-logistics material transfer process and a finite open queueing network to model the outbound logistics process within a manufacturing setup. The generalised expansion method (GEM) is employed to calculate network performance measures of the system, considering the blocking phenomenon. Discrete event simulation (DES) models are constructed using simulation software, integrating optimisation configurations to determine optimal buffer allocations to maximise system throughput. The findings of this study have significant implications for decision-making processes and offer opportunities to enhance the efficiency of manufacturing systems. By leveraging the proposed framework, organisations can gain valuable insights into supply chain performance, identify potential bottlenecks, and optimise buffer allocations to achieve improved operational efficiency and overall system throughput.

Fireline path optimisation in a heterogeneous forest landscape

International Journal of Wildland Fire · 2022-10-09

Background When fighting high-intensity wildfire, firefighters may construct a defensive fireline (fuel break) away from the raging front. The path of the fireline is the key to successful fire containment. However, the study of fireline path optimisation in the literature is limited. Aims We aim to find the optimal path for firefighting crews to encircle and contain a growing fire in the minimum time while keeping firefighters safe. Methods The model considers the realistic topographic factors that affect fire behaviour and fireline production rates. The forest landscape is partitioned into small homogeneous polygons according to their burning characteristics and modelled as a complex topological network using Delaunay triangulation. An algorithm is developed to find the fireline path for firefighting crews, traversing ‘safe’ edges of a dynamic network to meet at the earliest time at which the fireline path is completed. Key results Various experiments were conducted leading to insights on how the algorithm can be utilised to develop more effective firefighting strategies. Conclusions The proposed algorithm provides an efficient way to generate the optimal fireline path. Implications Future work could include the stochastic and dynamic factors in the system by considering probabilistic fire propagation and fireline construction rates.

Fleet Sizing of Heterogeneous Fleet of Trucks in a Material Handling System Using Anylogic Simulation Modelling

2022-07-26 · 3 citations

The focus of manufacturing organisations on their core competencies has placed third-party logistics service providers (3PL) in an ideal position to deal with supportive activities such as material handling, transportation, and storage using their expertise and economies of scale. This study considers the problem of determining the optimal fleet size of heterogeneous trucks to be outsourced from a 3PL to fulfil the demand of various raw materials requirements by a production facility while achieving a minimum total cost of these daily operations. Trucks are deployed in an interfacility material transportation system with different raw materials from designated storage areas to be transported to specified buffer locations per the production requirements. In a typical material forward flow, a truck undergoes many sub-processes with stochastic service times that vary with the type of material it carries and the type of the truck. Each material encompasses different physical attributes and specific job routings. Within this context, the inter-facility transportation process is modelled as a closed queueing network (CQN), and a mathematical model is developed to determine the optimal number of heterogeneous trucks to be outsourced from a 3PL while fulfilling the production requirements. A Discrete event simulation model, using Anylogic simulation software, is employed for solving the model to determine the optimal fleet size of trucks and their specific heterogeneous composition. Moreover, the simulation model is used to determine the main performance measures of the system, such as sub-process response times, queue lengths, cycle times, resource utilisations and bottlenecks, to assist in the decision-making process.

Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks

Operations Research Perspectives · 2022 · 16 citations

• Computer Science
• Computer Science
• Mathematical optimization

Material handling systems (MHS) are integral to logistics functions by providing various supports such as handling, moving, and storing materials in manufacturing and service organisations. This study considers determining the optimal size of a homogeneous fleet of trucks to be outsourced (or subcontracted) from a third-party logistics provider to be used daily to cyclically transport different types of raw materials from designated storage yards to intermediate buffer locations to be fed as inputs to a production facility for processing. Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. Furthermore, a discrete event simulation (DES) model is developed to validate the optimisation of non-dominant solutions. The proposed analytical approach, along with the simulation, are implemented in a real case study of a steel manufacturing setup. Analytical model results are validated using the simulation results, which are proved to be very accurate, with deviations ranges within ±7%.

Integer Programming $$\sum c_j\delta _j, \delta _j \in \ \{0,1\} \ \ \forall j$$

Springer optimization and its applications · 2021-01-01

Simultaneous machine selection and buffer allocation in large unbalanced series-parallel production lines

International Journal of Production Research · 2021 · 28 citations

• Computer Science
• Mathematical optimization
• Computer Science

Simultaneous optimisation of machines and buffers in a large series-parallel production line is an NP-hard problem. The formulated optimisation model in this study is used to minimise the total investment cost subject to the desired throughput rate and cycle time by optimising the machine types, number of parallel machines, and buffer capacities. To solve this kind of design problem, a decomposition-coordination method is proposed to efficiently and accurately generate allocation solutions for large production lines. The proposed method includes two iterative processes: the decomposition process decouples the original line into several small lines and optimises them separately, while the coordination process ensures that the optimisation problems of the decomposed lines are similar to the corresponding part of the original. The performance of this approach is demonstrated through numerical experiments by comparisons with the simulated annealing algorithm and non-dominated sorting genetic algorithm-II. Finally, the sets of numerical results and a multi-factorial experimental analysis illustrate the influences of target system parameters on the resource configurations.

Queueing network models for intelligent manufacturing units with dual-resource constraints

Computers & Operations Research · 2021-01-08 · 11 citations