混流装配线平衡问题的多目标优化方法研究

针对混流装配线存在的工序作业多、平衡难度大等问题,以U型布置的混装线为研究对象,兼顾工作站平均负荷和瞬时负荷平衡,在最小化工作站数的基础上均衡了工作站间和工作站内不同产品的作业负荷,建立U型混流装配线多目标平衡优化模型,同时提出目标法解决联合目标中的目标函数兼容性问题。设计并运用改进的自适应遗传算法求解模型,考虑到交叉、变异操作的随机性,在变异阶段加入强制规则,并对新生成的子代个体进行基因冲突检测,以提高可行解的比率。算例研究的结果表明本文所提的多目标优化方法能够较好地解决混装线平衡问题。     

多目标装配线平衡的优化算法

在生产制造系统中，装配线的平衡需要针对多个目标，传统的装配线平衡问题，优化单一目标，忽略了目标之间的联系。优化一个目标的同时，劣化了另外一个目标。章研究了多目标装配线平衡问题，探讨了这些目标之间的联系，设计了禁忌搜索算法求解多目标装配线的平衡问题。章从生产管理系统的角度优化多目标装配线平衡，与单一目标相比，具有显的改进。     

考虑产品与单元匹配的单元装配系统构建模型

针对日本式单元生产过程中流水装配线向单元装配系统转换的决策优化问题,本文以最小化总完工时间和工人总工时为目标,同时考虑产品与单元的匹配关系,构建了单元装配系统多目标优化模型,基于NSGA-II算法设计了适用于该问题的三段染色体的编码方式。通过算例分析了产品与单元匹配关系变化对总完工时间和工人总工时的影响,结果表明,在工人数不变的情况下,产品与单元匹配关系变化会导致总完工时间产生较大差异,随着工人数增多,这种差异逐渐变小。     

混合型装配线平衡问题求解方法研究

对混合型装配线平衡问题进行了描述和数学建模,提出一种启发式求解算法,求解目标是最小化工作站数目.为进一步优化求解结果,对启发式算法求解的结果进行仿真研究,分析各工作站的工作率、等待率和阻塞率,并以此为依据调整部分作业任务的分配,允许不同品种产品的相同作业任务安排在不同的工作站中,以对求解结果进行修正,进一步均衡各工作站的作业量.该求解方法既简化了求解过程,又兼顾到了系统的瞬时特性和作业任务的不可拆分性对求解结果的影响,实例分析验证了方法的有效性.     

双目标可重入混合流水车间调度问题的离散灰狼优化算法

可重入混合流水车间调度问题普遍存在于许多高科技制造产业中,如半导体晶圆制造和TFT-LCD面板生产过程等,但目前关于可重入调度问题的相关研究还比较少。本文设计了一种改进多目标灰狼优化算法(IMOGWO)解决最小化最大完工时间和总拖期时间最小的可重入混合流水车间调度问题,针对该问题特点对基本灰狼优化算法进行了一系列改进操作。通过对小规模测试问题基准算例的数值实验,验证了所设计的IMOGWO算法求解该调度问题的有效性。实验结果表明IMOGWO算法在非劣解的收敛性和支配性方面显著优于已有的NSGA-II和MOGWO算法,在解的分布性指标方面IMOGWO稍微优于其他两种算法。     

第II类双边拆卸线平衡问题建模与优化

报废汽车体积大,废弃物污染大,拆卸过程复杂,将作业任务均衡分配难。为此,本文对工作站数量确定的双边拆卸线平衡问题进行研究,建立问题数学模型,设计一种变邻域蛙跳算法。所提算法在寻优过程中采用变邻域搜索提高族群局部搜索效率;引入个体学习机制加快精英个体进化速度;提出基于二分法的节拍时间调整策略加快对最优节拍的搜索。最后,通过算例对算法性能进行验证并通过实例说明任务在拆卸线上平衡分配的重要性。     

随机型混合模式装配线平衡问题的集束搜索算法

本文提出了基于集束搜索的算法来解决随机型混合模式装配线平衡问题,目标是总费用最小化。给出的算例表明本文提出的算法与Prem Vrat的相比可以得到更好的结果。     

多式联运分运人选择的模型和算法

在对多式联运分运人选择问题分析的基础上,运用图论技术构建了基于联运分运人选择的多式联运网络。综合考虑了运输的规模经济性、时效性、风险性和联运联盟的稳定性,建立了基于综合运输成本最小、运输风险最小和合作强度最大的多目标优化选择模型。通过主要目标法,将模型转化为单目标模型。借鉴生物免疫原理,设计了基于克隆增扩的人工免疫算法对问题进行求解。最后通过算例对方法进行了验证。     

基于多目标规划的飞机路径恢复最优化算法研究

本文针对同一机场中同机型的多架飞机受到干扰后, 飞机路径恢复的多目标最优化问题进行研究。首先根据航空公司实际航班调整的常用原则和航班干扰管理的基本思想, 基于连接网络建立多目标规划模型, 其中两个目标按照优先级排列:第一个目标为最小化航班的最大延误时间, 第二个目标为最小化参与交换的飞机数量。然后根据该问题的航班波结构特点, 结合求解多目标规划的分层序列法, 分析优化问题的若干最优性质, 并基于快速排序算法和最小费用路算法设计出多项式算法。最后用算例验证了算法的有效性。该研究结果可以为航空公司减少航班延误提供理论和技术支持。     

随机需求下选址——库存问题

在由多个零售商和多个分销中心组成的供应链网络中，零售商的数量及位置已给定，零售商处的顾客需求是随机的。优化决策是确定分销中心的数量和位置、每个分销中心负责的零售商组、各零售商的订货策略，目标是使系统长期运行下的总成本达到最小。将这种选址——库存问题建模为整数线性规划模型，利用拉格朗日松弛方法和启发式算法分别获得问题的上下界，然后设计求解算法，并通过大量的算例考察算法的有效性。     

Optimal workforce assignment to operations of a paced assembly line

We study a paced assembly line intended for manufacturing different products. Workers with identical skills perform non-preemptable operations whose assignment to stations is known. Operations assigned to the same station are executed sequentially, and they should follow the given precedence relations. Operations assigned to different stations can be performed in parallel. The operation’s processing time depends on the number of workers performing this operation. The problem consists in assigning workers to operations such that the maximal number of workers employed simultaneously in the assembly line is minimized, the line cycle time is not exceeded and the box constraints specifying the possible number of workers for each operation are not violated. We show that the general problem is NP-hard in the strong sense, develop conventional and randomized heuristics, propose a reduction to a series of feasibility problems, present a MILP model for the feasibility problem, show relation of the feasibility problem to multi-mode project scheduling and multiprocessor scheduling, establish computational complexity of several special cases based on this relation and provide computer experiments with real and simulated data.     

A genetic algorithm of determining cycle time for printed circuit board assembly lines

The problem of allocating components to a printed circuit board (PCB) assembly line, which has several non-identical placement machines in series, is formulated as a minimax-type integer programming (IP) model in this paper. In order to achieve the best production throughput, the objective of the model is to minimize the cycle time of the assembly line. The IP model is proven to be NP-complete (non-deterministic polynomial), so a genetic algorithm (GA) is developed for the cycle time determination problem in this paper. Finally, the efficiency of the genetic algorithm is illustrated by a numerical example.     

Minimizing the number of workers in a paced mixed-model assembly line

We study a problem of minimizing the maximum number of identical workers over all cycles of a paced assembly line comprised of m stations and executing n parts of k types. There are lower and upper bounds on the workforce requirements and the cycle time constraints. We show that this problem is equivalent to the same problem without the cycle time constraints and with fixed workforce requirements. We prove that the problem is NP-hard in the strong sense if $m=4$ and the workforce requirements are station independent, and present an Integer Linear Programming model, an enumeration algorithm and a dynamic programming algorithm. Polynomial in k and polynomial in n algorithms for special cases with two part types or two stations are also given. Relations to the Bottleneck Traveling Salesman Problem and its generalizations are discussed.     

A new diversity induction mechanism for a multi-objective ant colony algorithm to solve a real-world time and space assembly line balancing problem

Time and space assembly line balancing considers realistic multi-objective versions of the classical assembly line balancing industrial problems. It involves the joint optimisation of conflicting criteria such as the cycle time, the number of stations, and/or the area of these stations. The different problems included in this area also inherit the precedence constraints and the cycle time limitations from assembly line balancing problems. The presence of these hard constraints and their multi-criteria nature make these problems very hard to solve. Multi-objective constructive metaheuristics (in particular, multi-objective ant colony optimisation) have demonstrated to be suitable approaches to solve time and space assembly line balancing problems. The aim of this contribution is to present a new mechanism to induce diversity in an existing multi-objective ant colony optimisation algorithm for the 1/3 variant of the time and space assembly line balancing problem. This variant is quite realistic in the automative industry as it involves the joint minimisation of the number and the area of the stations given a fixed cycle time limit. The performance of our proposal is validated considering ten real-like problem instances. Moreover, the diversity induction mechanism is also tested on a real-world instance from the Nissan plant in Barcelona (Spain).     

Metaheuristic algorithms for balancing robotic assembly lines with sequence-dependent robot setup times

Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequence-dependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.     

校车站点及线路的优化设计

以高校新校区教师校车站点及线路安排为对象,首先针对乘车站点建立了双目标非线性规划模型,其中目标函数包括乘客到达站点的距离偏差最小与所有乘客到达站点的总的距离最小两个方面;站点确定后针对车辆数最少、车辆行驶的总距离最短、各辆车的运行距离均衡及各辆车的负荷均衡这4个目标建立针对线路优化的多目标非线性规划模型,并给出了解决这类问题的启发式优化算法.与目前国内外研究相比较,该模型与算法更实际,更具体的给出了问题的解答.     

A mathematical programming model for the bus deviation route problem

In small towns, or in those peripherical metropolitan areas in which the demand for public transportation is relatively low, the objectives of the bus route planner are different from those faced in highly congested networks. Some towns, also in Italy, are experimenting with urban public transportation systems where regular bus routes are designed which allow users located at specific points outside the main line to signal their presence to the bus driver, who then deviates from the main route to satisfy this demand. This way the bus line is a mixture between a regular line and a dial-a-ride system. The bus deviation route problem is concerned with the design problem which arises in planning the location of the demand points outside the line. A model is presented which takes into account both the advantage of passengers served by this deviation device and the disadvantage suffered by passengers on the bus, whose travel time increases during deviations, and by passengers downstream of the deviation whose waiting time also increases. Through some modeling assumption we are able to represent this problem as a mixed integer linear programming problem, whose relatively low dimension allows for exact solution through standard simplex-based branch and bound code. The proposed model has been applied to a real case and some results of this are presented and discussed.     

Balancing two-sided U-type assembly lines using modified particle swarm optimization algorithm

In this paper, a new two-sided U-type assembly line balancing (TUALB) procedure and a new algorithm based on the particle swarm optimization algorithm to solve the TUALB problem are proposed. The proposed approach minimizes the number of stations for a given cycle time as the primary objective and it minimizes the number of positions as a secondary objective. The proposed approach is illustrated with an example problem. In order to evaluate the efficiency of the proposed algorithm, the test problems available in the literature are used. The experimental results show that the proposed approach performs well.     

An enumeration procedure for the assembly line balancing problem based on branching by non-decreasing idle time

In this article, we present a new exact algorithm for solving the simple assembly line balancing problem given a determined cycle time (SALBP-1). The algorithm is a station-oriented bidirectional branch-and-bound procedure based on a new enumeration strategy that explores the feasible solutions tree in a non-decreasing idle time order. The procedure uses several well-known lower bounds, dominance rules and a new logical test based on the assimilation of the feasibility problem for a given cycle time and number of stations (SALBP-F) to a maximum-flow problem.