Research Article
Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO
Algorithm 2
Procedure of SPFN-ACO.
S1. Initializes initial PVs population as all-zero vectors. The population size of is . The number of ants is . . | S2. For each PV, do: | S2.1. Each ants simultaneously finds its evacuation route under current PV by Simulation of Evacuation Process; | S2.2. All ants’ routes construct the corresponding evacuation plan under current PV and the objectives’ values | of this plan are calculated. | S3. Non-dominated sort PVs according to corresponding route plan’s objectives. And, select the top PVs. | S4. Update top PVs. The updated top PVs construct PVs population | S5. . | S6. For each PV in , do: | S6.1. Each ants simultaneously finds its evacuation route under current PV by Simulation of Evacuation Process; | S6.2. All ants’ routes construct the corresponding evacuation plan under current PV and the objectives’ values of this plan are | calculated. | S7. Update pheromone vectors in . The updated top pheromone vectors construct pheromone vectors population . | The and construct , namely . The population size of is . | S8. Non-dominated sort according to corresponding route plan’s objectives. And, select the top pheromone vectors to | construct new population . | S9. If , go to S5. Or else, terminate the algorithm and output final Pareto optimal set of evacuation plans. | Note: is the number of generations; is the maximum number of generations. |
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