The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, desirable performance of fault localization process in all-optical networks is presented by employing the recently introduced Monitoring-Trail (m-trail) (that was proved to yield better performance by establishing monitoring resources in a shape of trails). As well, a new technique for deploying m-trails on networks along with its established lightpaths to perform fault localization...
Vehicle Routing Problem has been approved a NP problem and it belongs to classical Combination Optimization hard problem. An effective algorithm based on Important Sampling is designed to solve the model which named Vehicle Routing Problem with Weight Coefficients and Stochastic Demands (WVRPSD). The optimal importance sampling distribution function was obtained by making use of the expection constructed...
The vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem, which has received considerable attention in recent years. In this paper, an effective meta-heuristics for VRPTW was designed to minimize the vehicle number and total travel distance. Performances are compared with other heuristics appeared in the literature recently by the bench-mark data sets...
Vehicle routing problem(VRP) is an NP-hard problem, Ant colony algorithm is an effective tool for solving combinatorial optimization problems like VRP. On the base of understanding VRP problem and Ant Colony Algorithm (ACA), analysis ACA's application in VRP, for its shortcomings, reference MMAS thought, introduce dynamic negative feedback mechanism and appropriate increase the visibility mechanism,...
In this paper we propose a tabu search heuristic embedded in adaptative memory procedure to solve the profitable arc tour problem (PATP). The PATP is a variant of the well-known vehicle routing problem in which a set of vehicle tours are constructed. The objective is to find a set of cycles in the tours of vehicle that maximize the collection of profits minus travel costs, which is in its turn subject...
The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. Vehicle Routing Problem has been approved a NP problem and it belongs to classical Combination Optimization hard problem. An effective algorithm based on cross-entropy is designed to solve the model which named Vehicle Routing Problem with Weight Coefficients and Stochastic...
The ant colony algorithm (ACA) has been successfully applied to several combinatorial optimization problems, but it has some shortcomings such as its slow computing speed, and it is easy to fall into local optimal. So a hybrid ant colony algorithm is proposed to optimize the ACA parameters. Firstly, the basic feasible solutions are solved by ACA, and then the quadratic optimal results are gotten by...
The logistic scheduling is a typical combinatorial optimization problem. Vehicle routing optimization is one of the most critical parts in logistics, and the Vehicle Routing Problem (VRP) is an important problem occurring in many distribution systems. This paper proposes an improved ant colony optimization algorithm to optimize the dynamic assignment to the Capacitated Vehicle Routing Problem (CVRP)...
In this paper, a multi-objective mathematical model was developed for the assignment of vehicles with minimizing three conflicting objectives. An alternative of variant split delivery strategy allowing the split demands could be delivered by more than one period, was used to cope the fluctuation over available multi-period customer demands. The proposed approach used a systematic method based on a...
We investigate the possibility of using kernel clustering and data fusion techniques for solving hard combinatorial optimization problems. The proposed general paradigm aims at incorporating unsupervised kernel methods into population-based heuristics, which rely on spatial fusion of solutions, in order to learn the solution clusters from the search history. This form of extracted knowledge guides...
The ant colony system (ACS) algorithm is vital in solving combinatorial optimization problems. However, the weaknesses of premature convergence and low efficiency greatly restrict its application. In order to improve the performance of the algorithm, the hybrid ant colony system (HACS) is presented by introducing the pheromone adjusting approach, combining ACS with saving and interchange methods,...
The vehicle routing problem is a central issue in transportation planning and optimization systems. The objective is to determine the most effective routes for a fleet of vehicles in order to service a set of geographically distributed customers while minimizing costs and adhering to capacity restrictions. Due to its inherent complexity, many heuristics have been proposed to solve this combinatorial...
Ant colony optimization (ACO) is a meta-heuristic approach to tackle hard combinatorial optimization problems. The basic component of ACO is a solution construction mechanism, which simulates the decision-making processes of ant colonies as they forage for food and find the most efficient routes from their nests to food sources. Due to its constructive nature, we hybridize the solution construction...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.