An integer linear programming model for the constrained shortest path tour problem

Andrade, Rafael; Saraiva, Rommel Dias

doi:10.1016/j.endm.2018.07.019

Cited by 17 publications

(6 citation statements)

References 6 publications

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“…Linear programming is an appropriate algorithm for these types of problems due to its simplicity and accuracy. In [11], researchers used the linear programming method for finding the shortest path in the weighted graph. Researchers in [12] used centralized simulated annealing algorithm to find the optimal path by considering traffic congestion.…”

Section: Related Workmentioning

confidence: 99%

An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution

Ghaffari¹,

Rahmani

Saberikamarposhti

et al. 2022

IEEE Access

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Finding the shortest and cleanest path in the cities is vital, especially in metropolises. Although several algorithms and some software have been introduced to manage the traffic or suggest a path with minimum traffic congestion, none considers air quality a deciding factor. This paper introduces a novel algorithm to find the shortest path based on traffic congestion and air quality. In the proposed algorithm, the city map is fetched from the Google Map app and is converted into a weighted graph. Traffic data is collected from GPS devices, which will be available through the local cloud services. The C-means clustering method is used to cluster traffic congestion. Also, the air quality information is collected from air pollution monitoring stations. The graph weights are calculated based on both air quality and traffic congestion factors, simultaneously. Finding the shortest path problem is then defined as an optimization problem, and the linear programming method is used to solve it. Finally, the proposed algorithm's performance is evaluated by finding the shortest path in Tehran, Iran in different scenarios.

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Section: Related Workmentioning

confidence: 99%

An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution

Ghaffari¹,

Rahmani

Saberikamarposhti

et al. 2022

IEEE Access

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“…4.3.1). In our context, a valid approximation cost g h i is represented by the cost of a shortest path tour solution, i.e., g h i can be set equal to lb h i computed in (8).…”

Section: A * Implementationmentioning

confidence: 99%

A generalized shortest path tour problem with time windows

Pugliese

Ferone²,

Festa³

et al. 2022

Comput Optim Appl

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This paper studies a generalization of the shortest path tour problem with time windows (GSPTPTW). The aim is to find a single-origin single-destination shortest path, which has to pass through an ordered sequence of not necessarily disjoint node-subsets. Each node has a time window for each node-subset to which it belongs. We investigate the theoretical properties of GSPTPTW and propose a dynamic programming approach to solve it. Numerical results collected on a large set of new benchmark instances highlight the effectiveness of the proposed solution approach.

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“…Liu et al [18] presented a branch-and-cut algorithm to study the two-echelon capacitated vehicle routing problem. Andrade and Saraiva [23] used shortest path method to solve an inter-linear programming model, which aims to find the shortest path between two vertices. A branch-and-cut algorithm was used to study the unit-demand capacitated vehicle routing problem [24].…”

Section: Literature Reviewmentioning

confidence: 99%

Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows

et al. 2019

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The sustainability and complexity of logistics networks come from the temporally and spatially uneven distributions of freight demand and supply. Operation strategies without considering the sustainability and complexity could dramatically increase the economic and environmental costs of logistics operations. This paper explores how the unevenly distributed demand and supply can be optimally matched through collaborations, and formulates and solves a Collaborative Pickup and Delivery Problem under Time Windows (CPDPTW) to optimize the structures of logistics networks and improve city sustainability and liverability. The CPDPTW is a three-stage framework. First, a multi-objective linear optimization model that minimizes the number of vehicles and the total cost of logistics operation is developed. Second, a composite algorithm consisting of improved k-means clustering, Demand-and-Time-based Dijkstra Algorithm (DTDA) and Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is devised to solve the optimization model. The clustering algorithm helps to identify the feasible initial solution to INSGA-II. Third, a method based on improved Shapley value model is proposed to obtain the collaborative alliance strategy that achieves the optimal profit allocation strategy. The proposed composite algorithm outperforms existing algorithms in minimizing terms of the total cost and number of electro-tricycles. An empirical case of Chongqing is employed to demonstrate the efficiency of the proposed mechanism for achieving optimality for logistics networks and realizing a win-win situation between suppliers and consumers.

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An integer linear programming model for the constrained shortest path tour problem

Cited by 17 publications

References 6 publications

An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution

An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution

A generalized shortest path tour problem with time windows

Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows

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