CAJ | 학술논문

机车车辆行业作为典型的面向订单的机械制造企业．优化的生产调度方法能提高订单的准时交货，缩短产品的生产周期，提高企业的市场竞争力。订单生产调度问题是典型的NP—hard问题。遗传算法（GeneticAlgorithms）为求具有多个约束的复杂问题提供了有效的方法。但是遗传算法的局部搜索能力比较差，在解决订单生产调度问题中存在着明显的不足。本文引入了局部搜索能力很强的禁忌搜索算法，用遗传算法和禁忌搜索算法相结合的混合遗传算法来解决机车车辆行业中面向订单生产调度问题。
궤차차량행업작위전형적면향정단적궤계제조기업．우화적생산조도방법능제고정단적준시교화，축단산품적생산주기，제고기업적시장경쟁력。정단생산조도문제시전형적NP—hard문제。유전산법（GeneticAlgorithms）위구구유다개약속적복잡문제제공료유효적방법。단시유전산법적국부수색능력비교차，재해결정단생산조도문제중존재착명현적불족。본문인입료국부수색능력흔강적금기수색산법，용유전산법화금기수색산법상결합적혼합유전산법래해결궤차차량행업중면향정단생산조도문제。
Locomotive and car enterprises as a typical scheduling Order, optimizing production scheduling methods can shorten production cycle, improve the market competitiveness of enterprises. Order scheduling problem is a typical NP-hard problem, in many cases a mathematical model is difficult to accurately solved. Genetic algorithms provides a common framework for solving complex problems. But the genetic algorithm in solving the order scheduling problem has obvious shortcomings. And the introduction of tabu search algorithm has strong local search ability.This paper explores using tabu search hybrid algorithm combining genetic algorithm to solve the problem of the scheduling order for locomotive and car enterprises.