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Rising international oil costs and the transport industry's recovery from the effects of Covid-19 resulted in the efficient management of fuel by logistics companies becoming a significant concern. One way of managing this is by... more
Rising international oil costs and the transport industry's recovery from the effects of Covid-19 resulted in the efficient management of fuel by logistics companies becoming a significant concern. One way of managing this is by analyzing the fuel consumption of trucks so as to better utilize the costly resource. Twenty-three driving data variables were gathered from 210 freight trucks and analyzed this data. Relevant variables that impact truck fuel consumption were extracted from the initial 23 variables gathered using stepwise regression, and then a prediction model was built from the identified relevant variables utilizing a binary logistic regression model. In addition, a back propagation neural network was employed in this study to create a second model of truck fuel use, and comparisons between the two models were made. The outcomes showed that the binary logistic regression model and the back-propagated neural network model prediction accuracy were 68.4% and 77.2%, respe...
Shortest path problem (SPP) has various applications in areas such as telecommunications, transportation and emergency services, and postal services among others. As a result, several algorithms have been developed to solve the SPP and... more
Shortest path problem (SPP) has various applications in areas such as telecommunications, transportation and emergency services, and postal services among others. As a result, several algorithms have been developed to solve the SPP and related problems. The current paper extends the TANYAKUMU labelling method for solving the Travelling salesman problem (TSP) to solve SPP in directed transportation networks. Numerical illustrations are used to prove the validity of the proposed method. The main contributions of this paper are as follows: (i) modification of TSP algorithm to solve single source SPP, (ii) the developed method numerically evaluated on four increasingly complex problems of sizes 11×11, 21×21, 23×23 and 26×26 and lastly (iii) the solutions obtained from solving these four problems are compared with those obtained by Minimum incoming weight label (MIWL) algorithm. The proposed algorithm computed the same shortest paths as the MIWL algorithm on all four problems.
The travelling salesman problem (TSP) is a problem whereby a finite number of nodes are supposed to be visited exactly once, one after the other, in such a way that the total weight of connecting arcs used to visit these nodes is... more
The travelling salesman problem (TSP) is a problem whereby a finite number of nodes are supposed to be visited exactly once, one after the other, in such a way that the total weight of connecting arcs used to visit these nodes is minimized. We propose a labelling method to solve the TSP problem. The algorithm terminates after K−1 iterations, where K is the total number of nodes in the network. The algorithm’s design allows it to determine alternative tours if there are any in the TSP network. The computational complexity of the algorithm reduces as iterations increase, thereby making it a powerful and efficient algorithm. Numerical illustrations are used to prove the efficiency and validity of the proposed algorithm.
Research Interests:
Research Interests:
We present a technique to solve the linear integer model with variable bounding. By using the continuous optimal solution of the linear integer model, the variable bounds for the basic variables are approximated and then used to calculate... more
We present a technique to solve the linear integer model with variable bounding. By using the continuous optimal solution of the linear integer model, the variable bounds for the basic variables are approximated and then used to calculate the optimal integer solution. With the variable bounds of the basic variables known, solving a linear integer model is easier by using either the branch and bound, branch and cut, branch and price, branch cut and price, or branch cut and free algorithms. Thus, the search for large numbers of subproblems, which are unnecessary and common for NP Complete linear integer models, is avoided.
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In this article, the authors propose a maximum flow algorithm based on flow matrix. The algorithm only requires the effort to reduce the capacity of the underutilized arcs to that of the respective flow. The optimality of the algorithm is... more
In this article, the authors propose a maximum flow algorithm based on flow matrix. The algorithm only requires the effort to reduce the capacity of the underutilized arcs to that of the respective flow. The optimality of the algorithm is proved by the max-flow min-cut theorem. The algorithm is table-based, thus avoiding augmenting path and residual network concepts. The authors used numerical examples and computational comparisons to demonstrate the efficiency of the algorithm. These examples and comparisons revealed that the proposed algorithm is capable of computing exact solutions while using few iterations as compared to some existing algorithms.
Research Interests:
Research Interests:
Research Interests:
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So many algorithms have been proposed to solve the shortest path in road networks, in this paper, an algorithm is developed to solve shortest route problems. The algorithm is being demonstrated through solving of various network problems.... more
So many algorithms have been proposed to solve the shortest path in road networks, in this paper, an algorithm is developed to solve shortest route problems. The algorithm is being demonstrated through solving of various network problems. The principle of the algorithm consist in transforming the graph into a tree by means of arc and node replication, thereby expanding outwards from the source node considering all possible paths up to the destination node. The objective is to develop a method that can be applied in directed and non-directed graphs.
Research Interests: Mathematics and Algorithm
In this paper, a new allocation method to solve the knapsack problems is developed and demonstrated. The method makes use of all possible item combinations to produce the optimal solution. The allocation method is divided into two sub -... more
In this paper, a new allocation method to solve the knapsack problems is developed and demonstrated. The method makes use of all possible item combinations to produce the optimal solution. The allocation method is divided into two sub - allocations procedures namely, the initial allocation procedure and the objective allocation procedure. Existence of combinations is determined by the initial allocation whereas the optimality of allocation is determined by the objective allocation. The method is capable of computing all possible solutions to the problem.
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The critical path method (CPM) is a project modelling algorithm developed in the 1950s for scheduling project activities, it is used to determine the critical path through the calculation of three parameters thus, slack, earliest event,... more
The critical path method (CPM) is a project modelling algorithm developed in the 1950s for scheduling project activities, it is used to determine the critical path through the calculation of three parameters thus, slack, earliest event, latest event times for each activity. In this paper, we demonstrate how to use Tawanda's non-iterative optimal tree algorithm for shortest route problems (TA) to determine the critical path(s). We have also compared TA with the original critical path method (CPM) and the modified Dijksra's algorithm for critical path method in a project network (MDA). However, the study revealed that TA can compute the critical path more effectively since it is also effective in project networks with k-possible critical paths, moreover, it does not make use of the slack, earliest, and latest time parameters, since these calculations consume more time.