{"id":1627,"date":"2022-01-11T03:42:25","date_gmt":"2022-01-11T01:42:25","guid":{"rendered":"https:\/\/mwasalatmisr.com\/?page_id=1627"},"modified":"2024-12-29T17:01:27","modified_gmt":"2024-12-29T15:01:27","slug":"for-cities-2","status":"publish","type":"page","link":"https:\/\/mwasalatmisr.com\/ar\/for-cities-2\/","title":{"rendered":"\u0644\u0644\u0645\u062f\u0646 \u0648 \u0627\u0644\u062d\u0643\u0648\u0645\u0627\u062a"},"content":{"rendered":"
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“A developed Country is not a place where the poor have cars. It’s where the rich use public transportation”<\/strong><\/h1>\n

Enrique Penalosa, Mayor of Bogota<\/p>\n<\/div>\n<\/div>\n

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Solution components<\/h2>

\u062a\u0635\u0645\u064a\u0645 \u0634\u0628\u0643\u0627\u062a \u0627\u0644\u0646\u0642\u0644<\/span><\/i><\/a><\/h4><\/div>
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Such problem is formulated as an optimization problem involving the <\/span><\/span><\/span><\/h5>\n
minimization of all resources and costs related to the public transport system. The optimization problem is subject to user equilibrium on <\/span><\/span><\/span><\/h5>\n
public transport network as well as to the bus capacity constraints and a set of feasibility constraints on route length and line frequency. <\/span><\/span><\/h5>\n
The objective function is defined as the sum of operator\u2019s costs and users\u2019 costs. The input data are the public transport demand matrix, <\/span><\/span><\/span><\/h5>\n
the characteristics of road network, the operating and users unit costs. Outputs are routes and frequencies for the lines of the public <\/span><\/span><\/span><\/h5>\n
transport network. The performances of the network are estimated by a hyperpath transit assignment model, which reproduces the choice <\/span><\/span><\/span><\/h5>\n
behaviour of transit users. The solving procedure consists of a set of heuristics, which includes a first routine for the definition of the <\/span><\/span><\/span><\/h5>\n
roads and the zones to be served, a second step for the routes generation and then a genetic algorithm for finding a sub-optimal set of <\/span><\/span><\/h5>\n
routes and associated frequencies. The GA is implemented in the C# language as a parallel genetic algorithm while the fitness evaluation <\/span><\/span><\/span><\/h5>\n
requires computing, for each solution generated, the two terms of the objective function by simulating the public transport network with.<\/span><\/span><\/span><\/h5>\n\n\t\t<\/div>\n\t<\/div>\n<\/div><\/div>

Service planning and scheduling<\/span><\/i><\/a><\/h4><\/div>
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\u0646\u0638\u0645 \u0627\u0644\u0625\u062a\u0627\u062d\u0629<\/span><\/i><\/a><\/h4><\/div>
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Governance and controls<\/span><\/i><\/a><\/h4><\/div>
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Electric mobility<\/span><\/i><\/a><\/h4><\/div>
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