兵工自动化
兵工自動化
병공자동화
ORDNANCE INDUSTRY AUTOMATION
2014年
4期
8-11,21
,共5页
武器目标分配%遗传算法%蚁群算法%遗传-蚁群算法
武器目標分配%遺傳算法%蟻群算法%遺傳-蟻群算法
무기목표분배%유전산법%의군산법%유전-의군산법
weapon target assignment%genetic algorithm%ant colony algorithm%genetic-ant colony algorithm
针对传统算法很难满足大型水面舰艇编队防空武器的武器目标分配(weapon target assignment，WTA)问题，提出一种将遗传算法融入蚁群算法的混合算法。分析了遗传算法和蚁群算法的优缺点、利用遗传算法快速全局随机搜索能力生成一组粗略解，用其作为蚁群算法的初始信息素，再利用蚁群算法的并行性、正反馈机制，最后求得最优解，并对遗传-蚁群算法与蚁群算法、遗传算法这3种方法进行仿真比较。分析结果证明：遗传-蚁群算法用更少的时间获得最优的火力分配方案，缩短了武器系统反应时间，在求解质量方面有较大优势。
針對傳統算法很難滿足大型水麵艦艇編隊防空武器的武器目標分配(weapon target assignment，WTA)問題，提齣一種將遺傳算法融入蟻群算法的混閤算法。分析瞭遺傳算法和蟻群算法的優缺點、利用遺傳算法快速全跼隨機搜索能力生成一組粗略解，用其作為蟻群算法的初始信息素，再利用蟻群算法的併行性、正反饋機製，最後求得最優解，併對遺傳-蟻群算法與蟻群算法、遺傳算法這3種方法進行倣真比較。分析結果證明：遺傳-蟻群算法用更少的時間穫得最優的火力分配方案，縮短瞭武器繫統反應時間，在求解質量方麵有較大優勢。
침대전통산법흔난만족대형수면함정편대방공무기적무기목표분배(weapon target assignment，WTA)문제，제출일충장유전산법융입의군산법적혼합산법。분석료유전산법화의군산법적우결점、이용유전산법쾌속전국수궤수색능력생성일조조략해，용기작위의군산법적초시신식소，재이용의군산법적병행성、정반궤궤제，최후구득최우해，병대유전-의군산법여의군산법、유전산법저3충방법진행방진비교。분석결과증명：유전-의군산법용경소적시간획득최우적화력분배방안，축단료무기계통반응시간，재구해질량방면유교대우세。
As the traditional algorithm can’t properly solve the anti-air craft weapon target assignment problem of a grope of surface ships, a mixed algorithm which combines genetic algorithm with ant colony algorithm is presented. The advantage and disadvantage of genetic algorithm and ant colony algorithm are analyzed in detail. The optimal solution was obtained by using the parallelism and positive feedback mechanism. And the genetic-ant colony algorithm, genetic algorithm and ant colony algorithm were compared by simulating calculation. The result demonstrates that the genetic-ant colony algorithm is the most effective way to determine the optimal solution of fire assignment strategy, which reduces the weapon system response time, and has great advantage relating solution quality.
