An analytical hierarchy process-based approach to solve the multi-objective multiple traveling salesman problem

Trigui, Sahar; Cheikhrouhou, Omar; Koubâa, Anis; Zarrad, Anis; Youssef, Habib

doi:10.1007/s11370-018-0259-8

Cited by 13 publications

(12 citation statements)

References 33 publications

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“…Disaster management. after a forest fire, an earthquake, or an industrial accident, mobile robots could help rescue teams in their mission [30,31].…”

Section: The Final Version Of This Paper Is Published In Computer Sci...mentioning

confidence: 99%

A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy

Cheikhrouhou

Khoufi

2021

Computer Science Review

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133

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“…Disaster management. after a forest fire, an earthquake, or an industrial accident, mobile robots could help rescue teams in their mission [30,31].…”

Section: The Final Version Of This Paper Is Published In Computer Sci...mentioning

confidence: 99%

A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy

Cheikhrouhou

Khoufi

2021

Computer Science Review

Self Cite

133

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“…The proposed AHP-MTSP algorithm was designed to select the best result from three approaches namely the market-based approach, the RTMA approach and the balanced. However, for lack of space, we present here only the market-based approach and we refer the reader to paper [67][68][69] for more details.…”

Section: Optimized Rescue Plan Developmentmentioning

confidence: 99%

“…To illustrate the market-based approach, we considered a scenario with two robots, six targets, and two OFs (TTD and MT), with the weight vector W = {0.66, 0.33} (TTD has a priority two times greater than that of MT; Figure 7). More details about the market-based approach are described in our previous paper [67]. First, R1 chooses T1 and R2 chooses T5.…”

Section: Optimized Rescue Plan Developmentmentioning

confidence: 99%

A Cloud Based Disaster Management System

Cheikhrouhou

Koubâa

Zarrad

2020

JSAN

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The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.

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“…The goals of appointing missions in Lu and Yue's research were to reduce the total distance, whereas to minimize the difference between the longest and the shortest tour lengths, and the multi objectives problem was solved by lumping the two claims into a single penalty-like objective function [11]. Trigui et al provided an analytical hierarchy process-based approach to minimize three objectives: the total traveled distance, the maximum tour, and the deviation rate [12]. For model constraints, the most common one in the existing research is time window [13].…”

Section: Introductionmentioning

confidence: 99%

Region Division in Logistics Distribution With a Two-Stage Optimization Algorithm

Qian

Zhao

2020

IEEE Access

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When facing the problem of modern logistics distribution under the large-scale network, the reasonable delivery task allocation has become an important part. For this problem, this paper uses the idea of decentralized control to establish a region division model in logistics distribution and transforms it into the multiple traveling salesmen problem with constraints of the road network and task allocation. The optimization goal of the model is to minimize the sum of the distances for logistics transport agents traveling all demand points in the system, with the constraints on the equilibrium of commodity requirements in each sub region. Then, a two-stage algorithm is proposed to solve the model. In the first stage, the K-means clustering method is used to obtain a highly feasible initial solution; In the second stage, the initial solution is optimized by the algorithm which is combining swap algorithm and tabu search algorithm. In the two-stage solution evaluation, the TSP solution based on the Lin-Kernighan algorithm is applied to obtain the sets of demand points with ranking of the route and the corresponding shortest distances for each divided sub region. Finally, to verify the effectiveness of the proposed model and solving method, two cases are presented in this paper. The region division method in logistics distribution proposed in this paper not only helps to reduce the total distance, but also helps to balance the workload of the logistics transport agents, thereby making great potential to reduce logistics costs and improving the overall operational efficiency of logistics distribution.

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An analytical hierarchy process-based approach to solve the multi-objective multiple traveling salesman problem

Cited by 13 publications

References 33 publications

A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy

A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy

A Cloud Based Disaster Management System

Region Division in Logistics Distribution With a Two-Stage Optimization Algorithm

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