Rail network routing and scheduling using simulated annealing

Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.

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Towards autonomic computing:adaptive network routing and scheduling

International Conference on Autonomic Computing, 2004. Proceedings. ◽

10.1109/icac.2004.1301381 ◽

2004 ◽

Cited By ~ 4

Author(s):

S. Whiteson ◽

P. Stone

Keyword(s):

Network Routing ◽

Routing And Scheduling

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Implementasi Simulated Annealing untuk Penentuan Rute pada Jaringan

MATICS ◽

10.18860/mat.v13i2.12969 ◽

2021 ◽

Vol 13 (2) ◽

pp. 42-46

Author(s):

Gusti Eka Yuliastuti ◽

Citra Nurina Prabiantissa ◽

Agung Mustika Rizki

Keyword(s):

Simulated Annealing ◽

Simulated Annealing Algorithm ◽

Computer Network ◽

Travelling Salesman Problem ◽

Optimal Solution ◽

Network Routing ◽

Path Selection ◽

Travelling Salesman ◽

Routing Problem ◽

Stored Information

Abstract—Recently computer networks are increasingly complex. It needs to be a supporting device for network management such as a router. Router is a device that plays an important role in the routing process. In a router stored information in the form of routing paths, where the information includes data and which routers will be passed. In certain cases, a router can have more than one gateway. This is because the router needs to send data packets to several networks that have different segments. Such cases can be handled by using the appropriate routing path selection rules. The routing problem can be regarded as a traveling salesman problem (TSP), where a mechanism is needed to determine the shortest route to be traversed. The author implements the Simulated Annealing Algorithm because it can produce an optimal solution with light computing, so that the routing process can be more effective and efficient. Index Terms—Computer Network, Routing, Simulated Annealing, Travelling Salesman Problem Abstrak–-Jaringan komputer saat ini semakin kompleks. Perlu adanya suatu perangkat pendukung untuk manajemen jaringan seperti router. Router merupakan perangkat yang berperan penting dalam proses routing. Pada sebuah router tersimpan informasi berupa jalur routing, dimana informasi tersebut mencakup data dan router mana saja yang akan dilewati. Pada kasus tertentu, router dapat memiliki lebih dari satu gateway. Hal ini disebabkan karena router perlu mengirimkan paket data ke beberapa jaringan yang memiliki segmen berbeda. Kasus tersebut dapat ditangani dengan menggunakan aturan pemilihan jalur routing yang tepat. Permasalahan routing dapat dikatakan sebagai suatu permasalahan travelling salesman problem (TSP), dimana diperlukan suatu mekanisme dalam menentukan rute terpendek untuk dilalui. Penulis mengimplementasikan Algoritma Simulated Annealing karena dapat menghasilkan solusi yang optimal dengan komputasi ringan, sehingga proses routing dapat lebih efektif dan efisien. Kata Kunci—Jaringan Komputer, Penentuan Rute, Travelling Salesman Problem, Algoritma Simulated Annealing

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FREIGHT TRAIN ROUTING AND SCHEDULING IN A PASSENGER RAIL NETWORK: COMPUTATIONAL COMPLEXITY AND THE STEPWISE DISPATCHING HEURISTIC

Asia Pacific Journal of Operational Research ◽

10.1142/s0217595907001358 ◽

2007 ◽

Vol 24 (04) ◽

pp. 499-533 ◽

Cited By ~ 10

Author(s):

T. GODWIN ◽

RAM GOPALAN ◽

T. T. NARENDRAN

Keyword(s):

Computational Complexity ◽

Scheduling Problem ◽

Computational Results ◽

Freight Train ◽

Routing And Scheduling ◽

Rail Network ◽

Passenger Rail ◽

Train Routing ◽

Np Complete ◽

Passenger Trains

In many countries, freight trains have to share a rail network with passenger trains. In this paper, we consider a situation where passenger trains must adhere to a strict published schedule, whereas freight train movements can be inserted at any convenient time, without disrupting scheduled passenger trains. We propose an algorithm for the problem of routing and scheduling of a single freight train in a passenger rail network. However, the multiple freight train routing and scheduling problem is shown to be NP-complete, even for simplified instances. Specifically, we show that both routing and scheduling of freight trains are difficult, even when only two freight trains are considered. It is also difficult when freight train movements are restricted to reach their destinations with no idling permitted at intermediate stations. We have developed a Stepwise Dispatching Heuristic for routing and scheduling multiple freight trains in a passenger rail network. Computational results confirm the efficacy of our algorithm for single freight train routing and of the proposed Stepwise Dispatching Heuristic.

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Minimizing Metro Transfer Waiting Time with AFCS Data Using Simulated Annealing with Parallel Computing

Journal of Advanced Transportation ◽

10.1155/2018/4218625 ◽

2018 ◽

Vol 2018 ◽

pp. 1-17 ◽

Cited By ~ 2

Author(s):

Xiaobo Liu ◽

Minghua Huang ◽

Hezhou Qu ◽

Steven Chien

Keyword(s):

Parallel Computing ◽

Simulated Annealing ◽

Waiting Time ◽

Service Capacity ◽

Rail Network ◽

Urban Rail ◽

Passenger Flows ◽

And Performance ◽

Transfer Stations ◽

Computing Approach

Coordinating train arrivals at transfer stations by altering their departure times can reduce transfer waiting time (TWT) and improve level of service. This paper develops a method to optimize train departure times from terminals that minimizes total TWT for an urban rail network with many transfer stations. To maintain service capacity and avoid operational complexity, dispatching headway is fixed. An integrated Simulated Annealing with parallel computing approach is applied to perform the optimization. To demonstrate model applicability and performance, the Shenzhen metro network is applied, where passenger flows (i.e., entry, transfer, and exit) at stations are approximated with the automatic fare collection system (AFCS) data. Results show that the total TWT can be significantly reduced.

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