【摘要】：對(duì)旅游區(qū)人群導(dǎo)游的最優(yōu)路徑規(guī)劃,可有效提高旅游期間時(shí)間的利用率。對(duì)導(dǎo)游最優(yōu)路徑進(jìn)行規(guī)劃,需要對(duì)目標(biāo)函數(shù)進(jìn)行求解,計(jì)算出游覽起始點(diǎn)至目的景點(diǎn)的游覽路線,完成最優(yōu)路徑的規(guī)劃。傳統(tǒng)方法對(duì)規(guī)劃行為進(jìn)行分析,建立旅游區(qū)最優(yōu)人群局部動(dòng)態(tài)規(guī)劃的運(yùn)動(dòng)代價(jià)評(píng)估函數(shù),但忽略了對(duì)評(píng)估函數(shù)求解,導(dǎo)致規(guī)劃精度低。提出基于蟻群算法的旅游區(qū)最優(yōu)人群導(dǎo)游路徑規(guī)劃模型。依據(jù)影響旅游區(qū)最優(yōu)人群導(dǎo)游規(guī)劃的主要因素建立導(dǎo)游最優(yōu)路徑規(guī)劃曲折程度約束,給出導(dǎo)游路徑規(guī)劃時(shí)間約束、導(dǎo)游路徑總長(zhǎng)約束,對(duì)目標(biāo)函數(shù)進(jìn)行求解,計(jì)算出旅游人群游覽起始點(diǎn)至目的景點(diǎn)的游覽路線,以此為依據(jù)完成對(duì)旅游區(qū)最優(yōu)人群導(dǎo)游路徑規(guī)劃。實(shí)驗(yàn)結(jié)果表明,所提模型及最優(yōu)路徑規(guī)劃算法給出的路徑規(guī)劃結(jié)果更為優(yōu)化,具有較少的游覽規(guī)劃距離和較為緊湊的游覽過(guò)程安排。
[Abstract]:The optimal path planning of the tourist guide in the tourist area can effectively improve the utilization rate of the time during the tour. The optimal path of the guide is planned, the objective function needs to be solved, the tour route of the tour starting point and the destination is calculated, and the planning of the optimal route is finished. In the traditional method, the planning behavior is analyzed, and the motion cost evaluation function of the local dynamic programming of the optimal population in the tourist area is established, but the solution of the evaluation function is ignored, and the planning accuracy is low. The paper presents an ant colony algorithm-based tour guide path planning model. according to the main factors that influence the guide planning of the optimal crowd of the tourist area, the guide optimal path planning and winding degree constraint is established, the guide path planning time constraint and the guide path total length constraint are given, and the objective function is solved, And the tour route of the tour start point and the destination scenic spot is calculated, so that the guide path planning of the optimal crowd of the tourist area is completed according to the completion. The experimental results show that the proposed model and the optimal path planning algorithm are more optimized, with less travel planning distance and more compact tour schedule.
【作者單位】： 重慶師范大學(xué)涉外商貿(mào)學(xué)院;
【分類號(hào)】：F592.6;TP18

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