scholarly journals GRASP-Tabu Search Algorithms for the Route Planning Problem in Spatial Crowdsourcing

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0

With the speedy progress of mobile devices, a lot of commercial enterprises have exploited crowdsourcing as a useful approach to gather information to develop their services. Thus, spatial crowdsourcing has appeared as a new platform in e-commerce and which implies procedures of requesters and workers. A requester submits spatial tasks request to the workers who choose and achieve them during a limited time. Thereafter, the requester pays only the worker for the well accomplished the task. In spatial crowdsourcing, each worker is required to physically move to the place to accomplish the spatial task and each task is linked with location and time. The objective of this article is to find an optimal route to the worker through maximizing her rewards with respecting some constraint, using an approach based on GRASP with Tabu. The proposed algorithm is used in the literature for benchmark instances. Computational results indicate that the proposed and the developed algorithm is competitive with other solution approaches.

2021 ◽  
pp. 1-19
Author(s):  
Y. Yang ◽  
Y. Mao ◽  
R. Xie ◽  
Y. Hu ◽  
Y. Nan

ABSTRACT Emergency search and rescue on the sea is an important part of national emergency response for marine perils. Optimal route planning for maritime search and rescue is the key capability to reduce the searching time, improve the rescue efficiency, as well as guarantee the rescue target’s safety of life and property. The main scope of the searching route planning is to optimise the searching time and voyage within the constraints of missing search rate and duplicate search rate. This paper proposes an optimal algorithm for searching routes of large amphibious aircraft corresponding to its flight characteristics and sea rescue capability. This algorithm transforms the search route planning problem into a discrete programming problem and applies the route traceback indexes to satisfy the duplicate search rate and missing search rate.


Author(s):  
Takashi Hasuike ◽  
◽  
Hideki Katagiri ◽  
Hiroe Tsubaki ◽  
Hiroshi Tsuda ◽  
...  

This paper proposes a flexible route planning problem for sightseeing with fuzzy random variables for travel times and satisfaction with activities under general sightseeing constraints. Travel time between sightseeing sites and satisfactions with activities depend on weather and climate conditions, and on traveler fatigue, so both fuzzy random variables for travel times and satisfactions and traveler fatigue-dependence are introduced. Tourists are likely to plan favored without drastically changing from the optimal route under usual conditions such as fine weather that suddenly changes for the worse. A route planning problem is proposed to obtain a favorite route similar to the optimal route under usual conditions. Trapezoidal fuzzy numbers and order relations are introduced as a basic case of fuzzy numbers. From order relations, the proposed model is transformed into an extended model of network optimization problems. A numerical example is used to compare the proposed model to standard route planning problems in sightseeing.


Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.


2021 ◽  
Vol 11 (6) ◽  
pp. 681
Author(s):  
Alessia Bocchi ◽  
Massimiliano Palmiero ◽  
Jose Manuel Cimadevilla Redondo ◽  
Laura Tascón ◽  
Raffaella Nori ◽  
...  

Individual factors like gender and familiarity can affect the kind of environmental representation that a person acquires during spatial navigation. Men seem to prefer relying on map-like survey representations, while women prefer using sequential route representations. Moreover, a good familiarity with the environment allows more complete environmental representations. This study was aimed at investigating gender differences in two different object-position learning tasks (i.e., Almeria Boxes Tasks) assuming a route or a survey perspective also considering the role of environmental familiarity. Two groups of participants had to learn the position of boxes placed in a virtual room. Participants had several trials, so that familiarity with the environment could increase. In both tasks, the effects of gender and familiarity were found, and only in the route perspective did an interaction effect emerge. This suggests that gender differences can be found regardless of the perspective taken, with men outperforming women in navigational tasks. However, in the route task, gender differences appeared only at the initial phase of learning, when the environment was unexplored, and disappeared when familiarity with the environment increased. This is consistent with studies showing that familiarity can mitigate gender differences in spatial tasks, especially in more complex ones.


Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.


2020 ◽  
Vol 13 (1) ◽  
pp. 517-538 ◽  
Author(s):  
Pangwei Wang ◽  
Hui Deng ◽  
Juan Zhang ◽  
Mingfang Zhang

Advancement in the novel technology of connected vehicles has presented opportunities and challenges for smart urban transport and land use. To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper. First, considering the traffic signal timing and phase information collected by V2X, road section resistance values are calculated dynamically based on real-time vehicular driving data. Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. Finally, we design the test scenario with different traffic saturation levels and collect 150 sets of data to analyze the feasibility of the proposed method. The numerical results have shown that the average travel times calculated by the proposed optimal route are 8.97 seconds, 12.54 seconds, and 21.85 seconds, which are much shorter than the results of traditional navigation routes. This proposed model can be further applied to the whole urban traffic network and contribute to a greater transport and land-use efficiency in the future.


Author(s):  
Yannik Rist ◽  
Michael A. Forbes

This paper proposes a new mixed integer programming formulation and branch and cut (BC) algorithm to solve the dial-a-ride problem (DARP). The DARP is a route-planning problem where several vehicles must serve a set of customers, each of which has a pickup and delivery location, and includes time window and ride time constraints. We develop “restricted fragments,” which are select segments of routes that can represent any DARP route. We show how to enumerate these restricted fragments and prove results on domination between them. The formulation we propose is solved with a BC algorithm, which includes new valid inequalities specific to our restricted fragment formulation. The algorithm is benchmarked on existing and new instances, solving nine existing instances to optimality for the first time. In comparison with current state-of-the-art methods, run times are reduced between one and two orders of magnitude on large instances.


2021 ◽  
Vol 152 ◽  
pp. 107029
Author(s):  
Xing Wang ◽  
Ling Wang ◽  
Shengyao Wang ◽  
Jing-fang Chen ◽  
Chuge Wu

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