A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Trav...
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A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). Moreover, as for the algorithms, understandability and flexibility are necessary because field experts and field engineers can understand and adjust it to satisfy the field conditions. To meet these requirements, a Backtrack and Restart Genetic Algorithm (Br-GA) is proposed. This method combines Backtracking and GA having simple heuristics such as 2-opt and NI (Nearest Insertion) so that, in case of stagflation, GA can restarts with the state of populations going back to the state in the generation before stagflation. Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity.
Delivery route optimization greatly improves the delivery efficiency in terms of all resources including human resources and energy consumption. In our application scenario the distribution network requires solving se...
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Delivery route optimization greatly improves the delivery efficiency in terms of all resources including human resources and energy consumption. In our application scenario the distribution network requires solving several tens to hundreds (max. 1500-2000) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). Moreover, since domain experts have to adjust the solutions due to boundary conditions that can not be formally expressed (such as human convenience, road conditions, and social aspects), understandability and flexibility of the applied heuristics are necessary. To meet all these requirements, a Backtrack and Restart Genetic Algorithm (Br-GA) was proposed. This method combines Backtracking and GA having simple heuristics such as 2-opt and NI (Nearest Insertion) so that, in case of stagflation, GA can restarts with the state of populations going back to the state in the generation before stagflation. Here, a refinement of this algorithm is introduced, which aims at ensuring diversity of initial solutions, which are subject to mutation. We introduce a formal definition of a diversity degree as well as a technique to compose new random individuals, which follow a required degree of diversity.
A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Trav...
详细信息
A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (max. 1500-2000) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). To meet these requirements, a Backtrack and Restart Genetic Algorithm (Br-GA) is proposed and compared with conventional ones, especially such as an Inner Random Restart Genetic Algorithm (Irr-GA). This method combines Backtracking and GA having simple heuristics such as 2-opt and NI (Nearest Insertion) so that, in case of stagflation, GA can restarts with the state of populations going back to the state in the generation before stagflation. Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity. Especially as to optimality, Br-GA is superior to even Irr-GA.
A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (maximum 2 thousands or so) ...
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A delivery route optimization system greatly improves the real time delivery efficiency. To realize such an optimization, its distribution network requires solving several tens to hundreds (maximum 2 thousands or so) cities Traveling Salesman Problems (TSP) within interactive response time (around 3 seconds) with expert-level accuracy (below 3% level of error rate). To meet these requirements, an Inner Random Restart Genetic Algorithm (Irr-GA) method is proposed. This method combines random restart and GA that has different types of simple heuristics such as 2-opt and NI (Nearest Insertion). Including these heuristics, field experts and field engineers can easily understand the way and use it. Using the tool applying their method, they can easily create/modify the solutions or conditions interactively depending on their field needs. Experimental results proved that the method meets the above-mentioned delivery scheduling requirements more than other methods from the viewpoint of optimality as well as simplicity.
In pervasive computing, embedded systems have a possibility to be attacked by crackers, including 0-day attack, as well as enterprise systems. In particular, in a case where a cracker gets a root privilege, damages ar...
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In pervasive computing, embedded systems have a possibility to be attacked by crackers, including 0-day attack, as well as enterprise systems. In particular, in a case where a cracker gets a root privilege, damages are significant. To resolve this problem, Security-Enhanced Linux (SELinux) is useful. However, SELinux has a problem that is significant complexity for configuration because of too fine-grained access control. As a method for resolving this problem, SELinux Policy Editor (SEEdit) has been developed; this is a tool that simplifies the SELinux configuration. SEEdit uses the Simplified Policy Description Language (SPDL) as a policy description language. In the SPDL, we define new access permissions that integrate Access Vector Permissions (AVPs) employed in SELinux to provide access permissions in a security policy. Thus, we propose a set of access permissions named Integrated Access Permissions (IAPs), which enables the achievement of a good balance between reducing the workload of the configurations and guaranteeing security in SELinux. In addition, we evaluate our IAPs and show them almost secure.
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