More than half of company's logistic budget is spent for the transportation matter. Hence, applying the efficient way to distribute things is exactly needed for the transportation system in order to gain better pr...
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ISBN:
(纸本)9781538647394
More than half of company's logistic budget is spent for the transportation matter. Hence, applying the efficient way to distribute things is exactly needed for the transportation system in order to gain better profit. The combination of Dijkstra algorithm and sweep algorithm is a novel method that able to resolve optimal distribution route planning. As we gain from our research that by utilizing this method we achieve the reduction of both distance travel and trip's time. We are gaining better solution for 9.3% in distance travel and successful cutting time travel for 500% from the original trip's time.
CV. Jogja Transport is a company that distribute cakes "Sari Roti" in Yogyakarta, Indonesia. It has responsibility to distribute the cakes for every customer during the customers' time windows. The distr...
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CV. Jogja Transport is a company that distribute cakes "Sari Roti" in Yogyakarta, Indonesia. It has responsibility to distribute the cakes for every customer during the customers' time windows. The distribution problem of CV. Jogja Transport belongs to Vehicle Routing Problem with Time Window (VRPTW). This paper tries to solve the problem of CV. Jogja Transport by proposing "cluster first route second" algorithm of simple heuristic method. Then the algorithm is combined with sweep algorithm for clustering the customers and Mixed Integer Linear Programming (MILP) to select the best route so that it can minimize the distance of each cluster. The result indicate that implementation of sweep algorithm and MILP can reduce the distances and the fuel up to 10.95% and the travel distance up to 2.60%.
The Capacitated Vehicle Routing Problem (CVRP) is an optimization problem owing to find minimal travel distances to serve customers with homogeneous fleet of vehicles. Clustering customers and then assign individual v...
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The Capacitated Vehicle Routing Problem (CVRP) is an optimization problem owing to find minimal travel distances to serve customers with homogeneous fleet of vehicles. Clustering customers and then assign individual vehicles is a widely-studied way, called cluster first and route second (CFRS) method, for solving CVRP. Cluster formation is important between two phases of CFRS for better CVRP solution. sweep (SW) clustering is the pioneer one in CFRS method which solely depends on customers' polar angle: sort the customers according to polar angle;and a cluster starts with customer having smallest polar angle and completes it considering others according to polar angle. On the other hand, sweep Nearest (SN) algorithm, an extension of sweep, also considers smallest polar angle customer to initialize a cluster but inserts other customer(s) based on the nearest neighbor approach. This study investigates a different way of clustering based on nearest neighbor approach. The proposed Distance based sweep Nearest (DSN) method starts clustering from the farthest customer point and continues for a cluster based on nearest neighbor concept. The proposed method does not rely on polar angle of the customers like SW and SN. To identify the effectiveness of the proposed approach, SW, SN and DSN have been implemented in this study for solving benchmark CVRPs. For route optimization of individual vehicles, Genetic algorithm, Ant Colony Optimization and Particle Swarm Optimization are considered for clusters formation with SW, SN and DSN. The experimental results identified that proposed DSN outperformed SN and SW in most of the cases and DSN with PSO was the best suited method for CVRP.
A counter example is given for the solution of the linear-quadratic optimization problem with three-point boundary conditions. The example shows that the solution obtained in (Mutallimov et al. in Adv. Differ. Equ. 20...
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A counter example is given for the solution of the linear-quadratic optimization problem with three-point boundary conditions. The example shows that the solution obtained in (Mutallimov et al. in Adv. Differ. Equ. 2015: 233, 2015) by using a sweep method is not optimal.
The sweep algorithm for solving optimal control problem with multi-point boundary conditions is offered. According to this algorithm, the search of initial conditions is reduced to the solution of the corresponding sy...
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The sweep algorithm for solving optimal control problem with multi-point boundary conditions is offered. According to this algorithm, the search of initial conditions is reduced to the solution of the corresponding system of linear algebraic equations. A similar algorithm is proposed for the discrete case.
Attended home delivery services like online grocery shopping services require the attendance of the customers during the delivery. Therefore, the Vehicle Routing Problem with TimeWindows occurs, which aims to find an ...
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ISBN:
(纸本)9783031220388;9783031220395
Attended home delivery services like online grocery shopping services require the attendance of the customers during the delivery. Therefore, the Vehicle Routing Problem with TimeWindows occurs, which aims to find an optimal schedule for a fleet of vehicles to deliver goods to customers. In this work, we propose three sweep algorithms, which account for the family of cluster-first, route-second methods, to solve the Vehicle Routing Problem with Time Windows. In the first step, the customers are split into subsets such that each set contains as many as possible customers that can be served within one tour, e.g., supplied with one vehicle. The second step computes optimal tours for all assigned clusters. In our application, the time windows follow no special structure, and hence, may overlap or include each other. Further, time windows of different lengths occur. This gives additional freedom to the company during the planning process, and hence, allows to offer discounted delivery rates to customers who tolerate longer delivery time windows. Our sweep algorithms differ in the clustering step. We suggest a variant based on the standard sweep algorithm and two variants focusing on time window length and capacity of vehicles. In the routing step, a Mixed-Integer Linear Program is utilized to obtain the optimal solution for each cluster. The paper is concluded by a computational study that compares the performance of the three variants. It shows that our approach can handle 1000 customers within a reasonable amount of time.
Capacitated Vehicle Routing Problem (CVRP) is a variant of Vehicle Routing Problem (VRP), where CVRP is only considered the capacity restrictions, and the object is to minimize the cost of the vehicles serve all custo...
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ISBN:
(纸本)9781467375238
Capacitated Vehicle Routing Problem (CVRP) is a variant of Vehicle Routing Problem (VRP), where CVRP is only considered the capacity restrictions, and the object is to minimize the cost of the vehicles serve all customers. In this study, we proposed an approach which is hybrid two-phase sweep algorithm (SA) and greedy search for solving CVRP. At the first stage of SA, all customers are clustered by SA and define each cluster as a block. The second stage is to reconstruct each neighbour clusters based on the first stage. Then the greedy search is applied to minimize the cost of each vehicle. Finally, the computational result on standard instances show the proposed approach is effective.
Polygon overlay operations are used for various purposes, such as GIS searches and queries, VLSI, and basic geometric operations of intersection, union, and difference. There have been recent research articles present...
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Polygon overlay operations are used for various purposes, such as GIS searches and queries, VLSI, and basic geometric operations of intersection, union, and difference. There have been recent research articles presenting algorithms using the GPU to perform line segment intersection for geometric operations. We present two parallel algorithms implemented on the GPU that focus on the active list portion of the traditional serial plane sweep algorithm. The first algorithm uses a single block of threads to simulate the active list data structure in hardware;this algorithm is slow due to GPU thread block size limitations and synchronization points but demonstrates favorable time complexity. The second algorithm uses dynamic parallelism to remove synchronization and scales to utilize available GPU hardware (single GPU). We perform experiments on both synthetic and real-world datasets. The presented results show improvement in execution time with respect to recent algorithms and low memory usage compared to recent algorithms. We achieve speedups of up to 38.8 over the serial sweep line algorithm on real-world data.
The vehicle routing problem (VRP) with capacity constraints is a challenging problem that falls into the category of non-deterministic polynomial-time hard (NP-hard) problems. Finding an optimal solution to this probl...
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The vehicle routing problem (VRP) with capacity constraints is a challenging problem that falls into the category of non-deterministic polynomial-time hard (NP-hard) problems. Finding an optimal solution to this problem is difficult as it involves numerous possible route combinations and constraints. The Adaptive Large Neighborhood Search (ALNS) has been widely employed to solve VRPs by searching for optimal solutions using a variety of dynamic destroy and repair operators, which gradually improve the initial solution. This study investigates six alternative initialization mechanisms and one distinct acceptance criterion for ALNS as the selection of an initial solution in ALNS is a crucial factor affecting the efficiency of the search for feasible regions. The process combines ALNS with the aforementioned procedures, resulting in a hybrid of seven methods. To evaluate the performance of the initialization mechanism and acceptance criterion in ALNS, 50 capacitated vehicle routing benchmark instances are employed. High-dimensional problems are also included for more comprehensive analysis. The improvement in the accuracy of the solutions achieved by each variant is reported.
We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called product-of-independent-probability-escalatio...
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We formulate the estimation of monotone response surface of multiple factors as the inverse of an iteration of partially ordered classifier ensembles. Each ensemble (called product-of-independent-probability-escalation (PIPE)-classifiers) is a projection of Bayes classifiers on the constrained space. We prove that the inverse of PIPE-classifiers (iPIPE) exists, and propose algorithms to efficiently compute iPIPE by reducing the space over which optimisation is conducted. The methods are applied in analysis and simulation settings where the surface dimension is higher than what the isotonic regression literature typically considers. Simulation shows that iPIPE-based credible intervals achieve nominal coverage probability and are more precise compared to unconstrained estimation.
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