Cigarette Volume Package Production Scheduling Optimization Based On Improved Particle Swarm And Tabu Search

Cigarette volume package production are cigarette manufacturing’s twoimportant process, it’s technological equipment is general-purpose equipment ofcomplete set. Each volume package unit can produce simultaneously a brand cigaretteand for packaging,except so, different volume package unit production areindependent of each other， so the volume package production scheduling can betreated as flow shop scheduling problem.Because of the cigarette manufacturingenterprise production mode gradually changing from single species mass productionplan for many varieties of medium and small batch of ordering production, productionscheduling of cigarette manufacturing enterprises become complex increasingly.Atpresent cigarette factory in our country is mainly based on the experience of peopleand adopts manual scheduling method to arrange the cigarette manufacturing, isunable to solve the optimization of complex scheduling problem.Due to difficulty ofcigarette production schedule depends largely on the cigarette volume packageproduction scheduling, so the volume package production scheduling optimization hasvery important significance for cigarette manufacturing enterprises to realize manykinds of medium and small batch of flexible production, timely meet orders, improvecustomer satisfaction.According to the characteristics of the cigarette volume package production andscheduling, cigarette manufacturing production scheduling model is established, andthe improved particle swarm algorithm is optimized.The paper mainly put forward anew algorithm integrates the improved particle swarm optimization and tabu searchalgorithm,and selected topic has certain theoretical significance and engineeringapplication value.The major works of this paper are listed as follows.1） According to the characteristics of the cigarette volume packageproduction,three kinds of cigarette manufacturing production scheduling model isestablished.the three models are volume package production scheduling model thatonly consider brand distribution, volume package production scheduling model thatconsider brand distribution and production order and volume package productionscheduling model that Consider brand distribution and production order and switchtime.At last, using a dynamic penalty function to deal with constraints. 2） The paper proposes an improved adaptive particle swarm optimizationalgorithm(IAPSO integrates gradient search method, breeding method and the all-timeoptimal location information of the first N particles. Using classic function test, theexperimental results verify that the algorithm has better convergence speed andconvergence precision than those relevant algorithms.The improved algorithm is usedto solve the first model to verify the superiority of IAPSO.3） The paper research the coding of cigarette volume package productionscheduling and two kinds of neighborhood of the tabu search algorithm of mobilestrategy, then exploration researches the method that integrates the particle swarmoptimization (BPSO) and tabu search algorithm (TS),and propose Two-stageintelligent optimization algorithm. Example verified the superiority of integrating theimproved algorithm (IAPSO) and tabu search algorithm (TS).