【摘要】：針對(duì)柔性作業(yè)車(chē)間調(diào)度問(wèn)題,構(gòu)建了以最大完工時(shí)間和總加工能耗最小為優(yōu)化目標(biāo)的多目標(biāo)調(diào)度模型。發(fā)展了改進(jìn)的混合蛙跳算法,通過(guò)設(shè)計(jì)基于MPX(Maximum Preserved Crossover)操作和單親遺傳算法基因移位操作的局部更新策略,避免了算法的非法解產(chǎn)生和修整,加快了算法尋優(yōu)速率。并通過(guò)簡(jiǎn)化鄰域?qū)?yōu)策略對(duì)組內(nèi)最優(yōu)解進(jìn)行優(yōu)化,防止算法陷入局部最優(yōu)。通過(guò)求解某企業(yè)生產(chǎn)車(chē)間實(shí)例,得出了不同權(quán)重下的調(diào)度方案,并對(duì)比標(biāo)準(zhǔn)混合蛙跳算法下的最大完工時(shí)間和加工能耗,證明了算法的有效性。
[Abstract]:In order to solve the flexible job shop scheduling problem, a multi-objective scheduling model with the maximum completion time and minimum total machining energy consumption as the optimization objective is proposed. An improved hybrid frog jump algorithm is developed. By designing a local update strategy based on MPX (Maximum Preserved Crossover) operation and gene shift operation of partheno-genetic algorithm, the illegal solution generation and trimming of the algorithm are avoided, and the optimization rate of the algorithm is speeded up. By simplifying the neighborhood optimization strategy, the intra-group optimal solution is optimized to prevent the algorithm from falling into the local optimal solution. The scheduling scheme with different weights is obtained by solving an example of a production workshop in an enterprise. The maximum completion time and processing energy consumption under the standard hybrid frog jump algorithm are compared, and the effectiveness of the algorithm is proved.
【作者單位】： 江南大學(xué)物聯(lián)網(wǎng)技術(shù)應(yīng)用教育部工程研究中心;
【基金】：國(guó)家自然科學(xué)基金(61572238) 江蘇省杰出青年基金(BK20160001) 江蘇省產(chǎn)學(xué)研聯(lián)合創(chuàng)新資金-前瞻性聯(lián)合研究項(xiàng)目(BY2016022-24)
【分類(lèi)號(hào)】：TB497;TP18

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