总第２５９期计算机与数字工程ＶｏＬ３９Ｎ０．５２０１１年第５期Ｃｏｍｐｕｔｅｒ＆ＤｉｇｉｔａｌＥｎｇｉｎｅｅｒｉｌｌｇ１９
ｌ河ＩＤ系统实时高效ＡＬｏＨＡ防冲突算法研究与仿真＋
徐海峰姜晖
（电子工程学院合肥２３００３７）
摘要简要介绍了当前几种主要的ＡＬＯＨＡ算法基本思想和系统效能，详细讨论了间接估算自适应帧时隙（ＤＦｓＡ）算法的原理和帧长度调整方法，并就ＤＦＳＡ算法对未识读标签的估计方法进行了统计分析，最后基于Ｍａｔｈｂ对各种算法性能进行了仿真。结果表明，间接估算ＤＦＳＡ算法较其它算法更能使ＲＦＤ系统保持较高的系统效率，能够实时准确地识别标签。
关键词射频识别；舢ＬＯＨＡ算法；防冲突；系统效率
中图分类号ＴＰ３０１．６
ＲｅｓｅａｒｃｈａｎｄＳｉｍｕｌａｔｉｎｇｏｎＡＬＯＨＡＡｎｔｉ—ｃｏｌｌｉｓｉｏｎＡＩｇｏｒｉｔｈｍ
ｗｉｔｈＨｉｇｈｅｒＥｍｃｉｅｎｃｙｉｎＲｅａｌ—ｔｉｍｅｆｏｒＲＦＩＤＳｙｓｔｅｍ
ＸｕＨａｉｆｅｎｇＪｉａｎｇＨｕｉ
（ＥｌｅｃｔｒｏｎｉｃＥｎｇｉｎｅｅｒｉｒｌｇＩｎｓｔｉｔｕｔｅ，Ｈｅｆｅｉ２３００３７）
脚於ｔ哺ｃｔ１１１ｔｈｉｓｐａｐｅｒ，ｔｈｅｐｒｉｒｍｒｙｔｈｏｕｇｈｔｓａ１１ｄｐｅｒｆｏｍｌａｎｃｅｏｆｓｏｍｅｒａｄｉｏｆｒｅｑｕｅｎｃｙｉｄｅｎｔｉｆｉｃａｔｉｏｎＡＬＯＨＡ锄ｔｉ－ｃｏｌ—ｌｉｓｉｏｎａｌｇｏｒｉｔｈｎｌｓａｒｅｉｎｔｒｏｄｕｃｅｄｃｏｎｃｉｓｅｌｙｗｈｉｃｈａｒｅ谢ｄｅｌｙｕｓｅｄｃｕｒｒｅｎｔｌｙ．Ａｎｄｔｈｅｎ，ｔｈｅｅｓｓｅｎｔｉａｌｔｈｅｏｒｙｏｆｄｙ枷ｃｆｒａｒｎｅｓｌｏｔ舢力ＨＡａｌｇｏｒｉｔｈｍ（Ｄ融～）ｗｈｉｃｈｅｓｔｉｒｎａｔｅｓｔｈｅｎｕｒｎｂｅｒｏｆｔｈｅｔａｇｓｉｎｔｈｅｖａｌｉｄａｒｅａｏｆｔｈｅｒｅａｄｅｒｉｎｄｉｒｅｃｔｌｙａｎｄｔｈｅｆｒ锄ｅｓｉｚｅａｄｊｕｓｔｉｎｇｍｅｔｈｏｄａｒｅｄｉｓｃｕｓｓｅｄｉｎｄｅｔａｉＬＩｔｉｓａｌｓｏａｍｌｙｚｅｄｓｔａｔｉｓｔｉｃａｌｌｙｆｏｒｅｓｔｉｒｍｔｉｎｇｔｈｅｎ啪ｂｅｒｏｆｒｅｓｉｄｕａｌｔａｇｓｗｈｉｃｈａｒｅｆｒｅｑｕｅｎｔｌｙａｄｏｐｔｅｄｉｎｔｈｅｄｙｎａｒｌｌｉｃｆｒ枷ｅｓｌｏｔＡ工妇ＨＡａｌｇｏｒｉｔｈ札Ｆｉｎａｌｌｙ，ａｎｔｈｅａｌｇｏｒｉｔｈｍｓａｒｅｓｉｌｌｌｕｌａｔｅｄｂａｓｅｄｏｎＭａｔ—ＬａｂａｎｄｔｈｅｒｅｓｕｌｔｓｉｎｄｉｃａｔｅｔｈａｔＤＦＳＡａｌｇｏｒｉｔｈｍｅｓｔｉｍａｔｉｎｇｔｈｅｎ啪ｂｅｒｏｆｒｅｓｉｄｕａｌｔａｇｓｉｎｄｉｒｅｃｔｌｙｃａｎｈａｖｅｔｈｅＲＦＤｓｙｓｔｅｍｋｅｅｐｈｉｇｈｅｒｅｆｆｉｃｉｅｎｃｙａｎｄｉｄｅｎｔｉｆｙｔｈｅｔａｇｓａｃｃｕｒａｔｅｌｙｉｎｒｅａｌ—ｔｉｍ己
ＫｅｙＷｂ咄ＲＦＤ，ＡＬｏＨＡａｌｇｏｒｊｔｈｍ，ａｎｔｉ—ｃｏｌｌｉｓｉｏｎ，ｓｙＳｔ咖ｅｆｆｉｃｉｅｎｃｙ
ＣＩａｓｓＮｌ耵１ｂ甘ＴＰ３０１．６
１引言在ＲＦＩＤ系统中，数据传输的完整性、正确性
且实时高效是确保整个系统性能的关键，而信道争
射频识别（ＲａｄｉｏＦｒｅｑｕｅｎｃｙＩｄｅｎｔｉｆｉｃａｔｉｏｎ，用即标签冲突，可能会使得阅读器接收到的标签信ＲＦＩＤ）技术［１］是一种利用无线通信实现的非接触息发生重叠，导致阅读器无法准确识别标签，大大式自动识别技术，堪称是２１世纪十大重要技术之降低了系统数据传输性能。因此，标签防冲突算法一，也是全球学术界、工业界和有关标准化组织所已成为解决碰撞问题的关键所在，其通常可分为随关注的热点。ＲＦＩＤ技术广泛应用于工业自动化、机性算法和确定性算法［２］两种。随机性算法大都智能交通运输控制管理、物流等众多领域，特别是采用ＡＩ．０ＨＡ机制，该算法是标签利用随机时间在大批量、高密集的军械仓储信息化管理及军事单响应阅读器的查询，其较确定性算法而言实现简／，７位门禁管理系统中，也拥有广阔的应用前景。单，成本较低，实时性高。安全性能好［３］，本文重点
－收稿日期：２０１０年１１月３日，修回日期：２０１０年１２月１０日
作者简介：徐海峰，男，硕士研究生，研究方向：ＲＦＤ及嵌入式系统设计。姜晖，男，教授，研究方向：高速数据采集与实时信号处理、嵌入式技术。
徐海峰等：ＲＦＤ系统实时高效ＡＬ（）ＨＡ防冲突算法研究与仿真第３９卷
对其进行研究并给出仿真结果。２
基于ＡＬＯＨＡ防碰撞算法
纯ＡＬＯＨＡ算法
纯ＡＬＯＨＡ算法的基本思想是当标签进入阅
读器工作区域被激活后，随机地在某时间点上发送信息。在标签发送数据的过程中，若有其他标签也在发送数据，则有可能使标签发送的信号重叠，导致完全碰撞或部分碰撞，从而使得阅读器无法正确识读标签。阅读器检测接收到的信号判断其有无碰撞发生。若发生碰撞，则发送命令让标签停止发送。标签等待随机长时间再重新发送标签自身序列号以减少碰撞；若没有冲突，则阅读器向标签发送一应答信号，使其转入休眠状态。此算法具有以下约束条件：
１）标签为主动式，即被激活后能够主动发送
信息，能够接收阅读器发送的命令；
２）标签周期循环地将一些数据发送给阅读器，数据传输时问只占循环周期的一小部分；
３）标签内部有一随机数发生器，能够实现标签随机延时发送自身信息；
４）标签被成功识别后将进入休眠状态，当其重新由非阅读器工作区域进入工作区域时可重新被激活，进而响应阅读器的命令。
纯ＡＬＯＨＡ算法的吞吐量为
Ｓ—Ｇ?Ｐ一２Ｇ
其中Ｓ为系统吞吐量，即一数据包长时间有效传输的实际总数据包数；Ｇ为输入负载，即一数据包长时间发送的总数据包数（阅读器工作区域标签总数）。仅当Ｇ一０．５时系统吞吐量达最大１８．４％，当负载增加时，性能急剧下降，系统吞吐量８０％以上未被利用。该算法实现简单，适用于标签数目较少、实时性要求不高的场合，但不能有效解决碰撞问题。
Ｓｌｏｔｔｅｄ
ＡＬＯＨＡ（ＳＡ）算法
ＳｌｏｔｔｅｄＡＬＯＨＡ（ＳＡ）算法Ｌ４］是基于ＡＬＯＨＡ
机制的一种改进算法，其基本思想是在ＡＬＯＨＡ算法的基础上将阅读器查询的时间段分割成多个离散时隙（ｓｌｏｔ），标签接收到阅读器的查询命令后，满足响应条件的标签随机选择其中一时隙向阅读器发送其自身携带的数据信息。每个时隙存在三种情况：无标签响应，即在此时隙没有标签发送数据信息；一个标签响应，即在此时隙内只有一个标签发送，标签能够被正确识别；多个标签响应，即在
此时隙内有多个标签发送，产生碰撞。此算法的约束条件有：
１）阅读器对各时隙实现时钟同步，并且时隙数由阅读器控制；
２）标签能计算时隙，内部具有时隙计数器和伪随机数发生器各一个；
３）标签响应阅读器命令时，只能在每个时隙起始处开始发送数据；
４）每个时隙时间长度要大于标签回复的数据长度。
与纯ＡＬＯＨＡ算法相比，ＳＡ算法中标签或成功发送或完全碰撞，避免了部分碰撞，提高了信道利用率。ＳＡ算法的吞吐量为Ｓ＝Ｇ?Ｐ～，当Ｇ一１时，系统的吞吐量可以达到最大值３６．８％，比纯ＡＩ。０ＨＡ算法提高了一倍。
ＦｒａｍｅＳｌｏｔｔｅｄＡＬＯＨＡ（ＦＳＡ）算法
ＦｒａｍｅＳｌｏｔｔｅｄ
ＡＬＯＨＡ（ＦＳＡ）算法是基于
ＡＬＯＨＡ机制的另一种改进算法，其基本思想是：在ＳＡ算法的基础上把Ｎ个时隙组成一帧，标签在查询帧内随机选择一个时隙发送数据，并且帧长Ｎ固定，由阅读器预先设定。ＳＡ算法中的约束条件在此算法中同样有效。经分析可知ＦＳＡ算法的吞吐量最大值也为３６．８％。
以上基于ＡＬＯＨＡ的三种标签防冲突算法有着共同的缺点，即当标签数量远大于时隙个数时，读取标签的时间会大大增加，系统吞吐量急剧减小；而当标签个数远小于时隙个数时，则会造成时隙的浪费。
２．４自适应的ＦＳＡ算法
为了弥补前三种算法的不足，使信道容量始终保持在较高利用率，使系统吞吐量一直保持在较高水平，有人提出了一种自适应的ＦＳＡ算法［５］，即
ＤｙｎａｍｉｃＦｒａｍｅＳｌｏｔｔｅｄ
ＡＩ。ＯＨＡ（ＤＦＳＡ）算法。
ＤＦＳＡ算法中，阅读器能动态改变（增加或减少）下
一次阅读周期中帧时隙总数Ｎ。改变帧长度方法主要有以下三种：
１）初始帧长由阅读器预先设定，之后帧长度根据前次查询统计的空闲时隙、碰撞时隙及成功识别时隙的数目进行调整。当碰撞的时隙数目超过给定上限阈值时，阅读器就会在下一次查询时增加帧长；如果产生碰撞时隙数目比给定下限阈值还小，阅读器就会减小帧长。此种方法可以有效的识别标签，但当大量标签同时存在时，因该算法只能确定地改变帧长度，并不能较好的避免标签碰撞。
２０１１年第５期计算机与数字工程
２）初始帧长由阅读器预先设定，阅读器根据前次查询统计的空闲时隙、碰撞时隙及成功识别时隙数目，按照一定的方法估计出未识读的标签数。经研究表明，当帧长等于未识读标签数目时，ＲＦＩＤ系统的吞吐量会达到最大［６］。因此阅读器根据估计出的未识别标签的数目调整下一次查询命令中的帧长，使系统能够时刻保持在较高的识别率。其中估计未识读标签数目的方法有多种，后文将给予讨论并给出统计分析。
３）初始帧长由阅读器预先设置，通常取２或４，如果当前阅读周期内没有标签被成功识别，阅读器将在下一阅读周期中按照指数规律增加帧长，并且一直重复此过程直到有标签被成功识别。当一
个标签被成功识别后，阅读器将立即停止当前的阅读周期，而以最小的起始帧长开始下一个阅读周期。此方法当标签数目很少时可几乎无碰撞地识别所有标签，但当标签数目很大时，就不能达到较好的实时性。
３标签数目估计方法
３．１间接估算法
未识读标签间接估算法的基本思想是首先估计出当前阅读周期中碰撞的时隙数目以及每个碰撞时隙中平均的未识读标签数目，然后得出总的未识读标签数作为下一阅读周期的帧长。
定义如下参数：帧长Ｎ，即阅读器查询命令中帧时隙数目；阅读器作用范围内的标签总数行；系统效率Ｓ，即一帧内只有一个标签响应的时隙数目与帧长的比值；一帧内只有一个标签响应的时隙数Ｃ，；一帧内两个或两个以上的标签响应的时隙数即碰撞时隙数Ｇ；碰撞时隙内平均未识读标签数ｍ。
在阅读周期中，标签选择哪一时隙进行响应服从二项分布Ｂ（以，１／Ｎ）［７｜，则ｚ个标签同时在某一时隙响应时的概率为：
只一（：）（南）２（１一志）抽一神，ｚ∈［ｏ，竹］且ｚ∈ｚ（，）
则，系统效率
ｓ。一Ｐ，一竹（南）（?一南）ｈ－１’
对式（２）微分求极值即可得到当标签数目咒和帧长Ｎ基本相等时，Ｐ。可达到最大，即３６．８％。由切比雪夫定理可知，每个阅读周期读出的标签和帧长之比依概率收敛到Ｐ。，即（Ｃ１／Ｎ）一Ｐ。一＆。因
此，每一阅读周期结束后成功识别的标签个数期望值为Ｃ１一竹（１—１／Ｎ）”１。
Ｃ。＝Ｎ（１一Ｐ。一Ｐ１）
一Ｎ（，一（，一斋）”一寿（?一南）“１’）ｃ３，
对于帧内某一时隙数ｉ，由只可推知只｛ｚ个标签选择时隙ｉｌ有碰撞发生｝一只
ｚ—Ｏ，ｚ一１
则时隙ｉ中标签数目的期望为
优一圣ｚ职一万焉高Ｐ丽ｊ葡（５）
∑正ｉ（Ｎ—１）‘删
则当前阅读周期过后，尚未成功读取的标签数目可估计为
，ｚｏ—ｍ?ｅ—Ｎ塞ｚＧ（南）２（?一南）”２
鉴于ｚ的未知性，可使‰一，ｚ—Ｃ１，结果与式
（６）等效。
由于阅读器查询的时间段有限，所以在满足每一时隙都能确保标签有足够的时间响应阅读器命令的条件下，一帧中时隙数不可能取的太大，并且时隙数只能按指数规律取值。这里做如下约束：一帧中最多只能包含２５６个时隙。当按上述方法估计出未识读的标签数目不大于２５６时，则可根据具体情况选择合适的帧长Ｎ作为下一阅读查询的命令参数，使得系统始终能以较大的系统效率工作。然而当现场标签数７２远远大于２５６时，由上述方法估计出的未识读标签数‰可能比２５６大的多，而帧时隙数Ｎ最大为２５６，由Ｎ一２５６时系统效率和标签数目的性能曲线可知，系统实际的工作效率可能很小，即碰撞的时隙数较多。
为解决此问题，可在标签响应阅读器命令时做如下处理：
通过对标签分组（可由标签内部时隙数计数器控制实现）来限制部分标签响应，一次阅读循环中
各组依次进行响应，分组数和模数Ｍ可由下式求
肚｛垡盐篮笋ｉ
Ｎ－２５６（７）
此时系统效率表达式为
＆一南（南）（?一志）啼１’
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在简单介绍 了 rfid 系统结构和工作流程的基础上对其中的关键技术之一--标签防碰撞算法进行重点讨 论,概述了防冲突方案,在已有的 aloha 算法的基础上提出了一种.........
rfid系统实时高效aloha防... 6页 1下载券 基于时隙...基于aloha的rfid系统防碰撞算法研究 姓名:鄂艳辉 ...(读卡器及标签)的整个工作过程建立了matlab软件仿真.........
基于aloha改进的rfid标签防冲突算法研究_互联网_it计算机_专业资料 暂无评价|0人阅读|0次下载基于aloha改进的rfid标签防冲突算法研究_互联网_it计算机_专业资料。.........
rfid系统实时高效aloha防... 6页 1下载券 rfid系统...ri fd系统, 研究和验证前面提出的快速抗冲突算法。...然后针对各个模块进行设计输入和行为 级的仿真, 在.........
rfid系统中一种改良的防... 2页 免费 rfid系统实时高效aloha防... 6页 1下载...rifd系统 阅读 器防冲突算法研究 与分析 刘磊安 赖 声礼 刘畅 赖 晓铮 (.........
rfid系统实时高效aloha防冲... 6页 1财富值 rfid标签阅读器系统防冲突... ..图2 算法流程 满足 目标 sri 的迭 代次数 图5 识别距离变化情况 4 仿真 与.........
南京邮电大学 rfid标签防冲突算法研究与改进 小组成员: 陈硕易然 宫译淳 指导...完成情况 已成功利用omnet++仿真平台模拟aloha 算法,并用c语言进行aloha算法的.........
基于aloha的rfid防碰撞算法仿真与实现_计算机软件及应用_it计算机_专业资料。rfid多标签防碰撞技术研究,专注于rfid身份认证,防碰撞,所有权转移,群组rfid标签相关技术.........
目前标签防冲突算法主要集中在时分复用(tdma)方面,分为基于aloha 和基于树两大...器防冲突算法进行分类研究,比较其 仿真或者实验数据,为rfid系统的防冲突算法研究.........
用方法aloha算法和二进制树算法做了详细的研究,比较...高效的防冲突算法,以提高rfid 系统的防碰撞能力同时...进行了仿真实验.设计仿 ‘真环境为:根据深度优先.........
本文在分析研究以往两类 rfid 防冲突算法的基础上,结合两者的优点提出了一种 ...通过仿真与其它防冲突算法相比在识别数量稳定的情况下, 本文提出 的算法具有更好.........
本文围绕rfid系统防冲突算法展开研究。首先对rfid的发展历程、分类、特点、国内外...进一步对aloha算法及其发展的算法进 行仿真分析,在已有的随机算法的基础上提出了.........
射频识别系统中防冲突算法研究_专业资料。针对rfid系统中多标签冲突问题,提出利用多路存取理论解决的方案。对几种防冲突算法进行了比较并最终加以改进。aloha算法不能.........
基于改进aloha算法的rfid抗冲突问题_专业资料。由标签...分组的aloha算法,分析和仿真均证明该算法在标签数量...rfid系统实时高效aloha防... 31人阅读 5页 ........
详细的研究,并给出了标签防冲突算法 进一步研究的...提出了一些扩展的方法来改善aloha算法在 rfid系统中...理论分析 和仿真结果表明sibt算法的性能优于其他基于.........
理 论分析和仿真结果表明 sibt 算法的性能优于其他...广东电子工业研究院 东莞 523808
institute of ...现有的 rfid 防冲突算法可划分为基于 aloha 和基于.........
■ 24小时热门信息
rfid系统中一种改良的防... 2页 免费 rfid系统实时高效aloha防... 6页 1下载...rifd系统 阅读 器防冲突算法研究 与分析 刘磊安 赖 声礼 刘畅 赖 晓铮 (.........
rfid系统实时高效aloha防冲... 6页 1财富值 rfid标签阅读器系统防冲突... ..图2 算法流程 满足 目标 sri 的迭 代次数 图5 识别距离变化情况 4 仿真 与.........
目前标签防冲突算法主要集中在时分复用(tdma)方面,分为基于aloha 和基于树两大...器防冲突算法进行分类研究,比较其 仿真或者实验数据,为rfid系统的防冲突算法研究.........
基于aloha的rfid防碰撞算法仿真与实现_计算机软件及应用_it计算机_专业资料。rfid多标签防碰撞技术研究,专注于rfid身份认证,防碰撞,所有权转移,群组rfid标签相关技术.........
■ 相关热门内容
■ 热门推荐多方法仿真软件
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唯一同时支持离散事件、系统动力学以及基于智能体建模的仿真工具。
使用AnyLogic做以下仿真：
请向我们描写一下Anylogic的优势，我们将非常感激您的反馈。
AnyLogic是非常强大的用来创建复杂仿真模型的工具。我们一直致力于粗切削能力模型，拥有大量的SKU和生产线，AnyLogic多元化的特征和方法使得我们可以建模所有生产过程中的复杂情况。
在我们开发的过程中我们得到了出色的支持，总是及时和明确的。支持团队甚至开发了一些定制的例子来满足我们的需求。我们觉得AnyLogic是一款伟大的工具且有一支出色的支持团队。
Elisa Elena,
ITE-CONSULT
AnyLogic是一款强大的结合Java的仿真工具。我喜欢AnyLogic的速度、可变性和多功能性。
Mariana Dorigatti,
INGAR-CONICET
市场上最灵活的仿真建模工具- 1） 当需要定制模型时，可通过Java平台访问Java编程进行2）混合不同的建模方法。带有预设对象和建模块的函数库（本身具有极大的灵活性），在新版本中进行了持续改进和增强，以及支持顾客导向的功能，使得整个图形几乎完整的呈现在我眼前！
Stefan Bengtsson,
斯德哥尔摩
Anylogic是迄今为止最先进的系统复杂的仿真软件。它可以有效地被当代经济学、教学以及MBA课程教学、高级经理人和企业决策者采用，进行各个领域的高度复杂系统的建模。
Dmitry Katalevsky, 经济学博士，工商管理硕士课程讲师，高级经理 ,
Deloitte &Touche
我们选择AnyLogic是因为以下产品特点：灵活的行人建模能力，直观的用户接口，简单的编程，可视化，以及可以为分析收集大范围统计数据的能力。
在我们和AnyLogic团队合作期间，我们赞赏技术支持上的效率和质量、公司的工程师专家、和公司为客户改进产品的意愿。
Alexey Pashkevitch,
ITS Consulting
我们发现AnyLogic凭借其速度、灵活性、可编程性成为市场上最好的仿真平台。
Silviu Trebuian, Managing Director,
Simando科技研究室
AnyLogic有足够的灵活性来支持系统和政策研究。而且足够强大来产生独立的可以被他人使用来支持他们专业工作的应用。
Neil McEvoy,
HealthEngineer
仿真和建模是灾难和应急管理科学基础方法中的重要元素。AnyLogic提供了灾难和应急管理的专业方法，基于智能体建模和能模拟危害和风险、应急准备和响应努力、以及发布灾难恢复场景的工具
Ali Asgary,
Disaster & Emergency Management Program, York University
我接触AnyLogic产品的时间较短，但发展的速度很快。在某种程度上，这反映了产品本身的能力--能够使用系统提供的大量工具来图形化设计仿真模拟逻辑。然而，AnyLogic员工也在培训和支持中起到了很大的作用。技术团队甚至添加了语言自定义特性来更好的满足我的特定需求。
Roger Baugher,
TrAnalytics 有限责任公司
AnyLogic被证明是一款非常有用的工具，用它我可以使用不同的仿真方法，创建对最终用户直观而有吸引力的接口。大多数功能是可以预定义对象，但如果有必要你可以添加你自己的结构，它提供了这样的灵活性。它们的技术支持团队知识丰富且反应迅速;在我看来他们的支持是非常出色的。
Principal Informatics Scientist,
AstraZeneca Pharmaceuticals
AnyLogic的团队一直很积极的支持我的项目并能达到我们要求。我用AnyLogic软件工作不到1个月，我自信我一直在进步因为我不断的从支持团队那儿学到很多知识。AnyLogic支持团队对我而言是有才、快速、精力充沛和完全配备技术知识的。有AnyLogic完美的支持团队的指导和用户友好的软件，恐怕不会有人再艰难的学习仿真了。
Ching-synn Teo,
AMD (Advanced Micro Devices, Inc.)
AnyLogic提供的仿真建模走出了许多传统评估技术的局限性。这意味着，如果使用得当，将走出固有的旧学校思维的偏见。如果你想寻找做生意、理解问题、发展新策略的创新方法，那么你需要跟的上的评估工具。AnyLogic提供了这种灵活性。
Gerard Nelson,
RedHot Innovation
We were looking at the behavior of our shippers in the oil & gas industry, and we needed to model this without using hundreds of pages of code. AnyLogic was the optimal method, we could create agents, and especially dynamically create multiple agents, plus we used multimethod since there were other processes where we needed to use discrete event and system dynamics.
Dumitru Cernelev,
Stream Systems Ltd.
AnyLogic is both a user-friendly graphical environment and a multi-functional set of libraries for building simulation models. An ability to customize models with Java grants professional modelers with unlimited capabilities for problem-solving in any practical area.
Ruslan Sukhih,
Solver Robotics LLC
Many specialists take part in plant planning process today, with everybody having their own vision, which has to be considered. AnyLogic is the best tool both for getting the operational data about the future system and an opportunity to visualize the work of it. This allows all the project participants to concretize and detalise their perceptions of how future plant has to be designed, and as a result, avoid mistakes while implementing the project. When huge long-term investments are involved, avoiding bottlenecks allows to save a lot of money during the years of plant operation, and AnyLogic is the way to help us in it.
Nikita Shchedrov, Project Engineer,
Begarat LLC
AnyLogic has a nice object-oriented feature that allows you to create a component and reuse it, which is very useful to us, plus, the user interface has many built in charts. The most valuable feature of AnyLogic to me is to export a model, and let anyone run it on their computer without a software license.
Victor Chang, Software Engineer,
TSG Consulting has been a long time user of Arena simulation software, and a couple of years back we decided that we needed a more scalable and powerful simulation tool so we surveyed the market and spent around 6 months extensively testing a large number of simulation software packages.
AnyLogic was the tool that stood clear of the rest.
Our consultants have adopted AnyLogic with enthusiasm and we are seeing gains in their productivity and the quality of the models they produce.
To say we are pleased with AnyLogic is understating our enthusiasm for the product and as a company we look forward to a great future working with AnyLogic.
Peter Bodon, Technical Director,
TSG Consulting
AnyLogic is a tool where a modeler can implement any of his ideas. Easily, fast and with enjoyment. A special thanks to the AnyLogic documentation and Support Team! Their perfect work makes your induction into AL world smooth and happy!
Yuriy Pidvalny, ML-IS,
Kuehne + Nagel
We chose AnyLogic because we found that traditional techniques did not do just to what we were trying to model. When we saw AnyLogic, it was a great ah-ha moment to say this is the tool I need to solve the problems I am trying to solve.
The benefits of a multi-method modeling approach are that you can solve the problem more naturally. If you do not have the ability to do multi-method modeling, you end up creating all types of anomalies in your model, fitting the methodology rather than fitting the problem. Multimethod modeling is a great effective tool.
Bipin Chadha, Ph.D., Data Scientist,
AnyLogic is extremely powerful, state of the art simulation software.
The multimethod modeling capabilities and the ability to customize with Java are just two of the many reasons this software is so functional.
Mike Prince, Senior Operations Research Specialist,
BNSF Railway
We chose AnyLogic to tackle our large complex problem because of the multimethod models you can use, the mix of agent based, discrete event and system dynamics is a very useful combination. My favorite part of AnyLogic is all the dashboard features, the great charts and business intelligence you can get from the agents that are working in the model.
Kyle Johnson, Global Business Services, Advanced Analytics and Optimization,
AnyLogic was the clear choice after comprehensive evaluation of multiple systems and further prototyping in those that were shortlisted.
Furthermore, it continues to impress the deeper we get. There's no doubt the right simulation and modelling tool was selected for the majority of our current and future needs.
Jay Ta'ala, Senior Modeller, Supply Chain Analytics,
BHP Billiton Iron Ore
Although I am still a new user of AnyLogic, I have been very impressed with its flexibility, ease of use, and the multimethod capabilities. AnyLogic’s versatility and standard libraries allow us to address a large number of different business process automation questions very quickly and with one software tool. I also believe the ability to customize ours models with Java code is invaluable when modeling the complex interactions in today’s real-world systems and operations.
Dr. Gregory Kott, Principal Research Scientist,
PARC, A Xerox Company
We’ve been using AnyLogic probably for four years now. Most of my work time I was working with another academically based agent based modeling system. We were aware that AnyLogic existed, but only after a while did we think that maybe we should look at it instead of looking at the system we were using, and we found that it was easier for us to learn and to implement.
Neil McEvoy, Director,
Centre for Research in Healthcare Engineering
Multimethod modeling is the most important feature of AnyLogic. The biggest advantage for me was the capability for advanced healthcare modelling and simulation.
Geoff McDonnell, Director,
Adaptive Care Systems and Synergia
We have found AnyLogic to be powerful, robust, and suitable for a wide variety of modeling projects. The ability to model using any of the major paradigms (or a combination) allows us to tailor our models appropriately. The user interface is easy to understand for people of all levels of education and experience. AnyLogic's superb technical support has helped us to model very complex systems that we would not have been able to do otherwise.
Mark Kazmierczak,
Gryphon Scientific
I go back with AnyLogic to the very beginning: over ten years now. Ten years ago, AnyLogic was what I call the only industrial strength product that had a hope of doing both system dynamics, agent based, and discrete event in one package. As best as I can tell, it’s still the only package that has that capability. As we do more especially in the realm of agent based models, there are some open-source tools, but none of them has anything close to the functionality that AnyLogic does.
Dr. Mark Paich, Director,
PricewaterhouseCoopers LLP
One of the most important AnyLogic features is the ability to build our own libraries. We only have to build them once, but can use them multiple times in different models.
Gunnar Feldmann, Assistant Operations Research Specialist,
Norfolk Southern Corporation
We chose AnyLogic for three reasons, technology, support and people. I think AnyLogic has the best technology in the simulation software industry, it has the agent based, process based and system dynamics, plus it is written in Java, which means many available resources and ease of finding people who can model in AnyLogic since many know Java code. AnyLogic can be deployed on the internet, you can develop an AnyLogic model and easily share with colleagues, partners, etc.
Clark Chang,
Norfolk Southern Railway
We use simulation tools, including AnyLogic, to analyze alternative capital investment solutions in order to help decide on the best investment decision. AnyLogic has helped with that decision process by providing our company with a tool that is flexible/adaptable to build models in different groups within our company using the team license server.
We can easily use and combine multiple simulation methods to create the best modeling approach for each problem.
The built-in functionality allows for new users to get up and running quickly and the use of Java means advanced users are able to build and customize more complex models.
Jeremiah Dirnberger,
The benefit of agent based modeling in AnyLogic is to truly model our supply chain. Each of the agents we use in our simulation can correspond to vessels, distribution centers, ports of loading, ports of discharge, our retailers, etc. with their own behaviors. AnyLogic makes it easy for me to give our many agents their own customizable behaviors and let them interact together in a fully integrated software.
Beth Tyrie,
Fruit of the Loom, Inc
I have been using Anylogic for quite some time now and have been falling in love with it.
I have never seen such a powefull tool easily combing several modeling methods in a true and seemlessly integrated multimethod approach. Besides the functionality provided by the application I find the 'Get support' function very valuable. I have had a few cases where the response on my questions included a good
advice or explanation and in one case the reply included the model with the suggested changes already applied. All within a few days. Excellent service helping me to quickly
Erwin Spekschoor, Project Manager and Consultant,
Lean Six Sigma Company
AnyLogic helps predict risks and trade offs to support decision making. It allows the users to visualize and validate plant design to gain buy in and ensure future production capacity, and forecast future workforce needs and risks.
AnyLogic is very flexible, you can integrate it with many things. The software seems to evolve, and the developers listen to comments.
Wenchun Annie Wang, Industrial Engineer – Simulation,
We chose AnyLogic because of its flexibility. We have many customers in many industries that have very different requirements because their supply chains are different, and we’ve been very easily able to change our models quickly to interact with the customers. The agent based tool is very powerful for us, our automated robots are highly intelligent, so we want to represent those behaviors using the agent based approach inside the AnyLogic tool, and we have very large fleets, up to 500 robots in a system, and AnyLogic is able to handle the complexity of the interactions amongst those 500 robots and able to do computations efficiently.
Dr. Larry M. Sweet, CTO,
Symbotic LLC
AnyLogic is an easy to learn platform that is able to incorporate various modeling techniques to allow us to create powerful solutions for our clients.
Eric Rosenbaum, Experienced Associate,
PricewaterhouseCoopers LLP
I’ve been using AnyLogic for about three or four years now, and I found that it’s probably one of the better solutions out there for really being able to implement models if you don’t necessarily have a very extensive coding background to start with.
Joseph Simkins,
Battelle Memorial Institute
AnyLogic is a simulation package that provides value to users at all levels.
The visual UI allows entry level users to quickly develop insightful simulation models.
The ability to customize models with Java provides the flexibility and freedom for advanced users to develop highly detailed and complex models efficiently.
The integration of AnyLogic with such a widely known language such as Java makes it accessible to a very broad talent pool, and eases the learning curve for good programmers to become advanced AnyLogic users.
Paul Corry, Lead Simulation Analyst,
Aurecon Australia
AnyLogic offers wide analysis and business process optimization capabilities in comparison to the traditional analytical methods. Support of multiple methods allows the analyst to choose solutions relevant to the goals of simulation and the available statistics. Other important advantages of the system are the optimization module and GIS map integration.
Nikolay Begunov, PhD, Project Manager,
Ural Bank for Reconstruction and Development
I see modeling and simulation capabilities, especially agent-based modeling techniques, as critical to helping identify breakthroughs with complex phenomena associated with health care delivery. Integrating diverse types of data with multi-method simulation can advance our understanding of biological phenomena in order to deliver higher quality health care.
AnyLogic’s leadership in agent-based modeling, combined with its unique approach in a Java-based architecture, enables Health Services Consulting to navigate new territory and pursue cutting-edge projects now and in the future. I’m excited about the possibilities.
Roger A. Edwards, ScD, Vice-President,
Health Services Consulting Corporation
AnyLogic allows to describe processes and explain them to decision makers. Its advantages are the great flexibility in reproduction of problems and the possibility to use system dynamics, agent based and discrete event simulation in one model.
Romeo Placido, Director Hospital Radiology,
Azienda Sanitaria Provinciale di Messina
AnyLogic has been perfect for us because of its flexibility and multimethod approach. We are able to look at a lot of different types of interactions, that you couldn’t typically do with, for example, a discrete modeling software. We are able to address many different problems with just one tool, which is fantastic for us.
Allan Chegus, President,
Stream Systems Ltd.
I have seen a lot of simulation products and this is the only one that can combine all three methodologies. Plus, the ability to show all the graphic components has a great impact on who I present the models to. This allows AnyLogic to be THE choice for simulation modeling.
Kelvin Blyden, Supply Chain Analyst,
Campbell’s
I would recommend AnyLogic software because it is a mature platform that allows a combination of multimethod modeling paradigms, in a very user friendly and open manner. Plus it takes advantage of Java which is also a technically mature and secure way of building models. The advantages of agent-based modeling with AnyLogic is that you can combine it with other methods and combine existing knowledge with agent based approach. Also, it’s fairly user friendly, the facilities in the graphical user interface and development are very good.
Artem Parakhine,
PricewaterhouseCoopers LLP
AnyLogic is flexible: I don't feel hemmed in with any approach, and version 7 is a huge leap forward in the multimethod capability. We usually make changes with our eyes wide open thanks to AnyLogic!
Keith Stockman, Manager of Projects and Operations Research, General Medicine Program,
Monash Health
We use AnyLogic to understand better, improve and demonstrate how complex systems work. My personal favorite aspect of AnyLogic is the fact that it compiles the simulation models into a general purpose, fully object-oriented program language, like Java. Which allows us to embed optimization algorithms into simulations without writing unnecessary code.
Onur Dulgeroglu, Senior Analytics Engineer,
GE Global Research
AnyLogic has demonstrated the capability of going from an academic environment to helping develop realistic tools in the areas of resource optimization. The simulation framework provides the ability to use both agent-based and event-based methods to describe the stochastic behavior of machine-controlled and human-controlled objects. Furthermore, the flexibility of creating customized code and outputting multiple aspects of the simulation permits for developers to test aspects of the tools being developed. Finally, the support of AnyLogic (both in the purchasing and development phases) was tremendous.
Moises Sudit, Ph.D., Director, Information Fusion Group,
The competition is constantly getting tougher, and today you have to compete for a one-hundredth of a percent of a market share in many industries. That’s why AnyLogic is unique. It allows you to optimize business processes and rise your resource utilization rate up to the level unachievable for most of the competitors.
Alexey Mashanov, CTO,
Magnat Group
这是一个非常实用的建模软件，它提供了大量种类的建模方法。高速度的建模方法和好用的用户接口是它其中的优势。特别是基于智能体建模和行人库，在相关的领域是非常有用的。它是一款极好的建模软件。
Gao Xiang,
北京交通大学
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