Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network t...Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network towards more reliable, greener and in general more sustainable transportation modes in a potential world class university is proposed. “Smart mobility” in a smart city will significantly contribute to achieving the goal of a university becoming a world class university. In order to have a regular and reliable rail system on campus, we optimize the route among major stations on campus, using shortest path problem Dijkstra algorithm in conjunction with a computer software called LINDO to arrive at the optimal route. In particular, it is observed that the shortest path from the main entrance gate (Canaan land entrance gate) to the Electrical Engineering Department is of distance 0.805 km.展开更多
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK ...A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.展开更多
Dijkstra algorithm is a theoretical basis to solve transportation network problems of the shortest path,which has a wide range of application in path optimization.Through analyzing traditional Dijkstra algorithm,on ac...Dijkstra algorithm is a theoretical basis to solve transportation network problems of the shortest path,which has a wide range of application in path optimization.Through analyzing traditional Dijkstra algorithm,on account of the insufficiency of this algorithm in path optimization,this paper uses adjacency list and circular linked list with combination to store date,and through the improved quick sorting algorithm for weight sorting,accomplish a quick search to the adjacent node,and so an improved Dijkstra algorithm is got.Then apply it to the optimal path search,and make simulation analysis for this algorithm through the example,also verify the effectiveness of the proposed algorithm.展开更多
Multilevel image segmentation is a critical task in image analysis,which imposes high requirements on the global search capability and convergence efficiency of segmentation algorithms.In this paper,an improved Artifi...Multilevel image segmentation is a critical task in image analysis,which imposes high requirements on the global search capability and convergence efficiency of segmentation algorithms.In this paper,an improved Artificial Protozoa Optimization algorithm,termed the two-stage Taguchi-assisted Gaussian–Levy Artificial Protozoa Optimization(TGAPO)algorithm,is proposed and applied tomultilevel image segmentation.The proposed algorithm adopts a two-stage evolutionary mechanism.In the first stage,Gaussian perturbation is introduced to enhance local search capability;in the second stage,Levy flight is incorporated to expand the global search range;and finally,the Taguchi strategy is employed to further refine the optimal solution.Consequently,the global optimization performance and robustness of the algorithm are significantly improved.To evaluate the effectiveness of the proposed TGAPO algorithm,comparative experiments are conducted with representative optimization algorithms,including the Grey Wolf Optimizer(GWO)and Particle Swarm Optimization(PSO),in the context ofmultilevel image segmentation.The segmentation quality is assessed using the minimum cross-entropy function as the performance metric.Experimental results demonstrate that the TGAPO algorithm outperforms the comparison algorithms in terms of segmentation accuracy and convergence speed,and exhibits superior stability in high-threshold segmentation tasks.Furthermore,the proposedmethod achieves excellentmulti-threshold segmentation performance for color images and shows strong potential for practical applications.展开更多
A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to ...A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to point conduction problem based on the principle of minimum entropy generation. In the optimization, the arrangement of high thermal conductivity materials is variable, the quantity of high thermal-conductivity material is constrained, and the objective is to obtain the maximum heat conduction rate as the entropy is the minimum.A novel algorithm of thermal conductivity discretization is proposed based on large quantity of calculations.Compared with other algorithms in literature, the average temperature in the substrate by the new algorithm is lower, while the highest temperature in the substrate is in a reasonable range. Thus the new algorithm is feasible. The optimization of volume to point heat conduction is carried out in a rectangular model with radiation boundary condition and constant surface temperature boundary condition. The results demonstrate that the algorithm of thermal conductivity discretization is applicable for volume to point heat conduction problems.展开更多
The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ...The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ＂time-consuming and low efficiency＂ in Dijkstra algorithm with traversal search for each node, A＊ algorithm could help the taxi find the optimal path and bring convenience for traffic management.展开更多
An improved adaptive particle swarm optimization(IAPSO)algorithm is presented for solving the minimum makespan problem of job shop scheduling problem(JSP).Inspired by hormone modulation mechanism,an adaptive hormonal ...An improved adaptive particle swarm optimization(IAPSO)algorithm is presented for solving the minimum makespan problem of job shop scheduling problem(JSP).Inspired by hormone modulation mechanism,an adaptive hormonal factor(HF),composed of an adaptive local hormonal factor(H l)and an adaptive global hormonal factor(H g),is devised to strengthen the information connection between particles.Using HF,each particle of the swarm can adjust its position self-adaptively to avoid premature phenomena and reach better solution.The computational results validate the effectiveness and stability of the proposed IAPSO,which can not only find optimal or close-to-optimal solutions but also obtain both better and more stability results than the existing particle swarm optimization(PSO)algorithms.展开更多
Given a connected undirected graph G whose edges are labeled,the minimumlabeling spanning tree(MLST)problemis to find a spanning tree of G with the smallest number of different labels.TheMLST is anNP-hard combinatoria...Given a connected undirected graph G whose edges are labeled,the minimumlabeling spanning tree(MLST)problemis to find a spanning tree of G with the smallest number of different labels.TheMLST is anNP-hard combinatorial optimization problem,which is widely applied in communication networks,multimodal transportation networks,and data compression.Some approximation algorithms and heuristics algorithms have been proposed for the problem.Firefly algorithm is a new meta-heuristic algorithm.Because of its simplicity and easy implementation,it has been successfully applied in various fields.However,the basic firefly algorithm is not suitable for discrete problems.To this end,a novel discrete firefly algorithm for the MLST problem is proposed in this paper.A binary operation method to update firefly positions and a local feasible handling method are introduced,which correct unfeasible solutions,eliminate redundant labels,and make the algorithm more suitable for discrete problems.Computational results show that the algorithm has good performance.The algorithm can be extended to solve other discrete optimization problems.展开更多
This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment ...This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.展开更多
A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional an...A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.展开更多
The extension of Minimum Spanning Tree(MST) problem is an NP hard problem which does not exit a polynomial time algorithm. In this paper, a fast optimization method on MST problem——the Gradient Gene Algorithm is int...The extension of Minimum Spanning Tree(MST) problem is an NP hard problem which does not exit a polynomial time algorithm. In this paper, a fast optimization method on MST problem——the Gradient Gene Algorithm is introduced. Compared with other evolutionary algorithms on MST problem, it is more advanced: firstly, very simple and easy to realize; then, efficient and accurate; finally general on other combination optimization problems.展开更多
In this figure, it finds a vertex to another vertex k shortest path algorithm. Provided there are n vertices and edges in the diagram. If the path loops, the time complexity of the algorithm is allowed O（w ＋ n log 2...In this figure, it finds a vertex to another vertex k shortest path algorithm. Provided there are n vertices and edges in the diagram. If the path loops, the time complexity of the algorithm is allowed O（w ＋ n log 2 n ＋ kw log 2 k）. If the request path does not contain the loop, the time complexity of the algorithm O（kn（w ＋ n log2 n）＋ kw log2 k）. The algorithm utilizes a simple extension of the Dijkstra algorithm determined the end of the length of the shortest path to the other vertices, and then, based on these data, branch and bound method to identify the required path. Experimental results show that the actual running time has relations with the structure of FIG.展开更多
In this paper, the map of a network of air routes was updated by removing the non-optimal routes and replacing them with the best ones. An integer linear programming model was developed. The aim was to find optimal ro...In this paper, the map of a network of air routes was updated by removing the non-optimal routes and replacing them with the best ones. An integer linear programming model was developed. The aim was to find optimal routes in superspace based on performance-based navigation. The optimal routes were found from a DIJKSTRA algorithm that calculates the shortest path in a graph. Simulations with python language on real traffic areas showed the improvements brought by surface navigation. In this work, the conceptual phase and the upper airspace were studied.展开更多
The potential role of formal structural optimization was investigated for designing foldable and deployable structures in this work.Shape-sizing nested optimization is a challenging design problem.Shape,represented by...The potential role of formal structural optimization was investigated for designing foldable and deployable structures in this work.Shape-sizing nested optimization is a challenging design problem.Shape,represented by the lengths and relative angles of elements,is critical to achieving smooth deployment to a desired span,while the section profiles of each element must satisfy structural dynamic performances in each deploying state.Dynamic characteristics of deployable structures in the initial state,the final state and also the middle deploying states are all crucial to the structural dynamic performances.The shape was represented by the nodal coordinates and the profiles of cross sections were represented by the diameters and thicknesses.SQP(sequential quadratic programming) method was used to explore the design space and identify the minimum mass solutions that satisfy kinematic and structural dynamic constraints.The optimization model and methodology were tested on the case-study of a deployable pantograph.This strategy can be easily extended to design a wide range of deployable structures,including deployable antenna structures,foldable solar sails,expandable bridges and retractable gymnasium roofs.展开更多
This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of nodes.Themain objective was to del...This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of nodes.Themain objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static networks.Thus,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for MANETs.This paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in MANETs.The results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse networks.The theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional application.The adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of MANETs.Thus,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional methods.This paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.展开更多
文摘Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network towards more reliable, greener and in general more sustainable transportation modes in a potential world class university is proposed. “Smart mobility” in a smart city will significantly contribute to achieving the goal of a university becoming a world class university. In order to have a regular and reliable rail system on campus, we optimize the route among major stations on campus, using shortest path problem Dijkstra algorithm in conjunction with a computer software called LINDO to arrive at the optimal route. In particular, it is observed that the shortest path from the main entrance gate (Canaan land entrance gate) to the Electrical Engineering Department is of distance 0.805 km.
文摘A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.
基金supported by the"Taishan Scholarship"Construction Engineering and Shandong Province Graduate Innovative Project(SDYC08011).
文摘Dijkstra algorithm is a theoretical basis to solve transportation network problems of the shortest path,which has a wide range of application in path optimization.Through analyzing traditional Dijkstra algorithm,on account of the insufficiency of this algorithm in path optimization,this paper uses adjacency list and circular linked list with combination to store date,and through the improved quick sorting algorithm for weight sorting,accomplish a quick search to the adjacent node,and so an improved Dijkstra algorithm is got.Then apply it to the optimal path search,and make simulation analysis for this algorithm through the example,also verify the effectiveness of the proposed algorithm.
文摘Multilevel image segmentation is a critical task in image analysis,which imposes high requirements on the global search capability and convergence efficiency of segmentation algorithms.In this paper,an improved Artificial Protozoa Optimization algorithm,termed the two-stage Taguchi-assisted Gaussian–Levy Artificial Protozoa Optimization(TGAPO)algorithm,is proposed and applied tomultilevel image segmentation.The proposed algorithm adopts a two-stage evolutionary mechanism.In the first stage,Gaussian perturbation is introduced to enhance local search capability;in the second stage,Levy flight is incorporated to expand the global search range;and finally,the Taguchi strategy is employed to further refine the optimal solution.Consequently,the global optimization performance and robustness of the algorithm are significantly improved.To evaluate the effectiveness of the proposed TGAPO algorithm,comparative experiments are conducted with representative optimization algorithms,including the Grey Wolf Optimizer(GWO)and Particle Swarm Optimization(PSO),in the context ofmultilevel image segmentation.The segmentation quality is assessed using the minimum cross-entropy function as the performance metric.Experimental results demonstrate that the TGAPO algorithm outperforms the comparison algorithms in terms of segmentation accuracy and convergence speed,and exhibits superior stability in high-threshold segmentation tasks.Furthermore,the proposedmethod achieves excellentmulti-threshold segmentation performance for color images and shows strong potential for practical applications.
基金Supported by the National Key Basic Research Program of China(2013CB228305)
文摘A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to point conduction problem based on the principle of minimum entropy generation. In the optimization, the arrangement of high thermal conductivity materials is variable, the quantity of high thermal-conductivity material is constrained, and the objective is to obtain the maximum heat conduction rate as the entropy is the minimum.A novel algorithm of thermal conductivity discretization is proposed based on large quantity of calculations.Compared with other algorithms in literature, the average temperature in the substrate by the new algorithm is lower, while the highest temperature in the substrate is in a reasonable range. Thus the new algorithm is feasible. The optimization of volume to point heat conduction is carried out in a rectangular model with radiation boundary condition and constant surface temperature boundary condition. The results demonstrate that the algorithm of thermal conductivity discretization is applicable for volume to point heat conduction problems.
文摘The optimal path algorithm analysis of GPS navigation in taxi management system based on A＊ algorithm was introduced in this paper. Through improving the traditional Dijkstra algorithm and avoiding problems such as ＂time-consuming and low efficiency＂ in Dijkstra algorithm with traversal search for each node, A＊ algorithm could help the taxi find the optimal path and bring convenience for traffic management.
基金Supported by National Natural Science Foundation of P.R.China(50275150)National Research Foundation for the Doctoral Program of Higher Education of P.R.China(20040533035)
基金Supported by the National Natural Science Foundation of China(51175262)the Research Fund for Doctoral Program of Higher Education of China(20093218110020)+2 种基金the Jiangsu Province Science Foundation for Excellent Youths(BK201210111)the Jiangsu Province Industry-Academy-Research Grant(BY201220116)the Innovative and Excellent Foundation for Doctoral Dissertation of Nanjing University of Aeronautics and Astronautics(BCXJ10-09)
文摘An improved adaptive particle swarm optimization(IAPSO)algorithm is presented for solving the minimum makespan problem of job shop scheduling problem(JSP).Inspired by hormone modulation mechanism,an adaptive hormonal factor(HF),composed of an adaptive local hormonal factor(H l)and an adaptive global hormonal factor(H g),is devised to strengthen the information connection between particles.Using HF,each particle of the swarm can adjust its position self-adaptively to avoid premature phenomena and reach better solution.The computational results validate the effectiveness and stability of the proposed IAPSO,which can not only find optimal or close-to-optimal solutions but also obtain both better and more stability results than the existing particle swarm optimization(PSO)algorithms.
基金This work is supported by the National Natural Science Foundation of China under Grant 61772179the Hunan Provincial Natural Science Foundation of China under Grant 2019JJ40005+3 种基金the Science and Technology Plan Project of Hunan Province under Grant 2016TP1020the Double First-Class University Project of Hunan Province under Grant Xiangjiaotong[2018]469the Open Fund Project of Hunan Provincial Key Laboratory of Intelligent Information Processing and Application for Hengyang Normal University under Grant IIPA19K02the Science Foundation of Hengyang Normal University under Grant 19QD13.
文摘Given a connected undirected graph G whose edges are labeled,the minimumlabeling spanning tree(MLST)problemis to find a spanning tree of G with the smallest number of different labels.TheMLST is anNP-hard combinatorial optimization problem,which is widely applied in communication networks,multimodal transportation networks,and data compression.Some approximation algorithms and heuristics algorithms have been proposed for the problem.Firefly algorithm is a new meta-heuristic algorithm.Because of its simplicity and easy implementation,it has been successfully applied in various fields.However,the basic firefly algorithm is not suitable for discrete problems.To this end,a novel discrete firefly algorithm for the MLST problem is proposed in this paper.A binary operation method to update firefly positions and a local feasible handling method are introduced,which correct unfeasible solutions,eliminate redundant labels,and make the algorithm more suitable for discrete problems.Computational results show that the algorithm has good performance.The algorithm can be extended to solve other discrete optimization problems.
基金supported by the National Natural Science Foundation of China(61971470).
文摘This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.
基金The National Key Technology R&D Program of China during the 11th Five Year Plan Period(No.2008BAJ11B01)
文摘A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.
文摘The extension of Minimum Spanning Tree(MST) problem is an NP hard problem which does not exit a polynomial time algorithm. In this paper, a fast optimization method on MST problem——the Gradient Gene Algorithm is introduced. Compared with other evolutionary algorithms on MST problem, it is more advanced: firstly, very simple and easy to realize; then, efficient and accurate; finally general on other combination optimization problems.
文摘In this figure, it finds a vertex to another vertex k shortest path algorithm. Provided there are n vertices and edges in the diagram. If the path loops, the time complexity of the algorithm is allowed O（w ＋ n log 2 n ＋ kw log 2 k）. If the request path does not contain the loop, the time complexity of the algorithm O（kn（w ＋ n log2 n）＋ kw log2 k）. The algorithm utilizes a simple extension of the Dijkstra algorithm determined the end of the length of the shortest path to the other vertices, and then, based on these data, branch and bound method to identify the required path. Experimental results show that the actual running time has relations with the structure of FIG.
文摘In this paper, the map of a network of air routes was updated by removing the non-optimal routes and replacing them with the best ones. An integer linear programming model was developed. The aim was to find optimal routes in superspace based on performance-based navigation. The optimal routes were found from a DIJKSTRA algorithm that calculates the shortest path in a graph. Simulations with python language on real traffic areas showed the improvements brought by surface navigation. In this work, the conceptual phase and the upper airspace were studied.
基金Project(030103) supported by the Weaponry Equipment Pre-Research Key Foundation of ChinaProject(69982009) supported by the National Natural Science Foundation of China
文摘The potential role of formal structural optimization was investigated for designing foldable and deployable structures in this work.Shape-sizing nested optimization is a challenging design problem.Shape,represented by the lengths and relative angles of elements,is critical to achieving smooth deployment to a desired span,while the section profiles of each element must satisfy structural dynamic performances in each deploying state.Dynamic characteristics of deployable structures in the initial state,the final state and also the middle deploying states are all crucial to the structural dynamic performances.The shape was represented by the nodal coordinates and the profiles of cross sections were represented by the diameters and thicknesses.SQP(sequential quadratic programming) method was used to explore the design space and identify the minimum mass solutions that satisfy kinematic and structural dynamic constraints.The optimization model and methodology were tested on the case-study of a deployable pantograph.This strategy can be easily extended to design a wide range of deployable structures,including deployable antenna structures,foldable solar sails,expandable bridges and retractable gymnasium roofs.
基金supported by Northern Border University,Arar,Kingdom of Saudi Arabia,through the Project Number“NBU-FFR-2024-2248-03”.
文摘This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks(MANETs)from dynamic topologies that pose great challenges because of the mobility of nodes.Themain objective was to delve into and refine the application of the Dijkstra’s algorithm in this context,a method conventionally esteemed for its efficiency in static networks.Thus,this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm,considering adaptation to the dynamic network conditions that are typical for MANETs.This paper has shown through detailed algorithmic analysis that Dijkstra’s algorithm,when adapted for dynamic updates,yields a very workable solution to the problem of real-time routing in MANETs.The results indicate that with these changes,Dijkstra’s algorithm performs much better computationally and 30%better in routing optimization than Bellman-Ford when working with configurations of sparse networks.The theoretical framework adapted,with the adaptation of the Dijkstra’s algorithm for dynamically changing network topologies,is novel in this work and quite different from any traditional application.The adaptation should offer more efficient routing and less computational overhead,most apt in the limited resource environment of MANETs.Thus,from these findings,one may derive a conclusion that the proposed version of Dijkstra’s algorithm is the best and most feasible choice of the routing protocol for MANETs given all pertinent key performance and resource consumption indicators and further that the proposed method offers a marked improvement over traditional methods.This paper,therefore,operationalizes the theoretical model into practical scenarios and also further research with empirical simulations to understand more about its operational effectiveness.
