基于混合遗传算法的制造/再制造集成物流网络优化设计

为了合理设计制造／再制造混合系统中的集成物流网络结构，综合考虑网络中正向和逆向物流的设施集成与运输整合，建立了一种制造／再制造集成物流网络优化设计的混合整数非线性规划模型，以确定网络中各种设施的数量、位置及规模，并在由此构成的各条物流路径上合理分配物流量，目标是使运营周期内的净收益最大。提出了一种采用自适应交叉和变异操作的混合遗传算法对设计进行优化。最后，通过一个算例验证了所提模型及算法的有效性。     

产品回收多级逆向物流网络优化设计模型

为降低逆向物流成本,改善客户产品回收便利性,优化逆向物流网络中产品回收的渠道选择决策,在原有正向物流网络基础上,提出了包含初始收集点、集中回收中心和回收处理工厂三种物流设施的多级逆向物流网络.以总逆向物流成本最小为目标,兼顾各客户群的产品回收便利性,建立了0-1混合整数规划模型,实现逆向物流网络的选址/分配问题.应用遗传算法求解该模型.模拟算例表明,该算法有效且可行,为企业进行逆向物流网络设计提供可参考的模型和求解算法.     

Design of global supply chain network with operational risks

Facility location decisions play a vital role in the strategic design of the global supply chain. Global supply chains are vulnerable towards different types of risks factor that causes disturbance in the allocation of certain goods at the required place and time, and with the required quality and quantity. This paper presents a model of the multi-stage global supply chain network problem incorporating a set of risk factors (such as: late shipment, exchange rates, quality problems, logistics and transportation breakdown, and production risks), their expected values and probability of their occurrence, and associated additional cost. Different scenarios are considered to demonstrate the applicability of the model. Optimal decisions regarding the facility locations and inter-echelon quantity flows in the global supply chain are based on initial information for the risk factors. Further, if any change in the expected value of risk factor has occurred, the inter-echelons shifting take place to minimize the overall cost of the supply chain.     

再制造闭环物流网络优化设计模型

为提高再制造物流管理绩效，合理设计再制造物流网络结构，基于混合整数线性规划方法提出一种多产品、有能力限制的再制造闲环物流网络优化设计模型，据此确定网络中各种设施的数量和位置，并在由此构成的各条物流路径上合理分配物流量，目标是使计划期内的净收益最大。通过一个算例验证模型的有效性，并从正向和逆向物流设施的集成、正向和逆向物流运输的整合、回收处理技术的选择等方面讨论模型的进一步扩展。     

A mixed integer programming model for remanufacturing in reverse logistics environment

Recently, there has been a growing interest in reverse logistics due to environmental deterioration. Firms incorporate reverse flow to their systems for such reasons as ecological and economic factors, government regulations and social responsibilities. In this paper a new mixed integer mathematical model for a remanufacturing system, which includes both forward and reverse flows, is proposed and illustrated on a numerical example. The proposed model provides the optimal values of production and transportation quantities of manufactured and remanufactured products while solving the location problem of dissassembly, collection and distribution facilities. The model is validated by using a set of experimental data reflecting practical business situation. Sensitivity analysis of the model is also presented.     

An integrated planning approach for a nanodeposition manufacturing process

This paper deals with the planning problem in a nanodeposition manufacturing process, in which a toolbit that consists of a multilayer grid of micro/nanofluidic channels is used to deposit nanoscale liquid materials to desired positions on workparts to form solid patterns. The objective is to obtain a planning procedure that achieves efficient throughput for the studied nanodeposition manufacturing systems. We break down the studied problem into several sub-problems as design pattern decomposition, nanopore assignment, liquid material routing in the multilayer grid fluidic network, and toolbit path planning. Efficient algorithms are proposed to solve these sub-problems individually, and then finally integrated into a framework that systematically plans the nanodeposition manufacturing process. A software tool that plans, simulates, and controls the nanodeposition manufacturing process by implementing the proposed algorithms is reported in this paper.     

Designing and planning a multi-echelon multi-period multi-product closed-loop supply chain utilizing genetic algorithm

Designing and planning a closed-loop supply chain in a comprehensive structure is vital for its applicability. To cope with the design and planning issue of a comprehensive closed-loop supply chain network, this paper develops an extended model, which is multi-echelon, multi-product, and multi-period in a mixed integer linear programming framework. The word “comprehensive,” in our mathematical approach, in designing and planning a closed-loop supply chain problem, can be analyzed from two complementary angles: including all possible entities (facilities) of a real condition and considering minimum limitations on possible flows between entities. In our proposed model, customers can be supplied via manufacturers, warehouses, and distributors, as an example. The proposed model is solved by CPLEX optimization software and by a developed genetic algorithm. During this computational analysis, we compare results of proposed pretuned genetic algorithm with a global optimum of CPLEX solver. Then, a sufficient number of large-size instances are generated and solved by the proposed genetic algorithm. To the best of our knowledge, there has been no similar multi-period multi-product closed-loop supply chain design and planning problem utilizing any kind of meta-heuristics let alone genetic algorithms. Therefore, in this issue, it is an original research, and results prove the acceptable performances of the developed genetic algorithm.     

A robust design for a closed-loop supply chain network under an uncertain environment

This paper presents a robust design for a multi-product, multi-echelon, closed-loop logistic network model in an uncertain environment. The model includes a general network structure considering both forward and reverse processes that can be used in various industries, such as electronics, digital equipment, and vehicles. Because logistic network design is a time consuming and costly project as well as a strategic and sensitive decision (i.e. the change of such decision is difficult in the future), a robust optimisation approach is adopted to cope with the uncertainty of demand and the return rate described by a finite set of possible scenarios. Hence, to obtain robust solutions with better time, the scenario relaxation algorithm is employed for the proposed model. Numerical examples and a sensitivity analysis are presented to demonstrate the significance and applicability of the presented model. It is shown that solutions resulted from the suggested approach insure more situations, especially in worst case ones. The results show that although the profit values of the robust configuration are less than the deterministic configuration, the robust configuration is more reliable than the deterministic one because the deterministic configuration is infeasible under some demand and return rates (i.e. in the worst cases). Moreover, the results show the computing time superiority of the algorithm compared to the extensive form model as well as optimality of the resulted solutions.     

经销商从事再制造的多期闭环供应链网络均衡*

近年来,在工程机械和建筑设备等行业,出现了经销商从事再制造的实际案例。基于此,研究经销商从事再制造的多周期闭环供应链网络均衡问题。在每个规划期末,经销商承担废旧产品的回收,然后将一部分转卖给制造商,剩余部分用于自身的再制造;此外,考虑制造商能够在设计阶段确定产品的可再制造水平。利用变分不等式和拉格朗日对偶理论获得各层成员的Nash均衡条件,进而建立整个闭环供应链网络的均衡模型。通过修正投影收缩算法求解,结合算例分析经销商的再制造转化率和经销商销售给制造商的废旧品比例对各成员利润和再制造设计水平的影响。结果表明：在大多数情况下,经销商从事再制造对其自身有利,制造商利润降低,需要设计适当的机制实现系统的帕累托改进;随着再制造转化率的提高,经销商的收益逐渐改善,制造商的利润增加缓慢。     

制造/再制造集成物流网络设计的随机规划模型

为了合理设计制造／再制造混合系统中的集成物流网络结构，综合考虑网络中正向物流和逆向物流的设施集成与运输整舍，以及产品需求量和废旧产品回收量的随机性，提出了一种制造／再制造集成物流网络优化设计的两阶段补偿随机规划模型，用以确定网络中各种设施的数量及其位置，并在由此构成的各条物流路径上合理分配物流量，目标是使计划期内的净成本最小。算例验证了随机规划模型的有效性。     

制造/再制造混合系统中集成物流网络优化设计模型研究

为提高制造/再制造混合系统中的物流管理绩效,合理设计制造/再制造集成物流网络结构,基于混合整数线性规划方法,提出了一种制造/再制造集成物流网络优化设计模型,据此确定网络中各种设施的数量、位置及物流量分配,以使投资和运营的总成本最小.该模型的特点是：适合单产品、单周期、有能力限制的制造/再制造集成物流网络设施选址-分配问题.考虑了集成物流网络中共用设施的选址;正向物流中统筹考虑再制造产品和新产品的物流分配,但再制造产品和新产品不能相互替代.最后,通过一个算例验证了所提模型的有效性.     

Bi-objective heuristics for multi-item freights distribution planning problem in crossdocking networks

Crossdocking is a distribution strategy in which distribution centers operate as transfer points to harmonize the continuous physical flow through supply chain with the least storage. The coordination of this system in a network of crossdocks with multitype and time-restricted pickups and deliveries requires a complex planning. This paper addresses the distribution planning problem of crossdocking network, considering transshipment possibility among crossdocks and tardiness permission for some pickups. The problem is formulated as a bi-objective integer-programming model minimizing total transportation and holding costs and total tardiness. An innovative heuristic procedure to construct an effective initial solution and three improving algorithms based on appropriate meta-heuristics (variable neighborhood search, tabu search, and simulated annealing) is developed to solve the problem. Experimental results demonstrate the potency of proposed algorithms achieving remarkable results.     

An improved genetic local search algorithm for defect reconstruction from MFL signals

This paper presents an improved genetic local algorithm by incorporating the simulated-annealing technique into the perturbation process of the genetic local search algorithm and proposes an improved-genetic-local-search-algorithm-based inverse algorithm for two-dimensional defect reconstruction from the magnetic-flux-leakage signals. In the algorithm, a radial-basis-function neural network is utilized as a forward model, and the improved genetic local search algorithm is used to solve the optimization problem in the inverse problem. Experiments are presented to compare the proposed inverse algorithm with both the canonical-genetic-algorithm-based inverse algorithm and the genetic-local-search-algorithm-based inverse algorithm. The results demonstrate that the proposed inverse algorithm is more accurate and robust to the noise.     

Capacities-based supply chain network design considering demand uncertainty using two-stage stochastic programming

The design of a supply chain (SC) aims to minimize cost so the product can reach the customer at the cheapest cost with flexible demand. The demand of a product is variable with time and environment. Most of the researchers have considered investment cost, processing cost, and transportation cost as variable costs to minimize the cost while considering a constant demand. In actual practice, the demands are flexible. In this paper, a two-stage stochastic programming model has been proposed for a capacities-based network design of a supply chain for flexible demands while considering inventory carrying cost and missed opportunity cost in addition to the above-mentioned costs. It will enhance the logistic planning and seek the location network optimally. Furthermore, in the first stage, decision variables represent different nodes (facility locations of echelons) of the supply chain, with the assumption that they will be considered at the design stage before uncertain parameters are unveiled. On the other hand, decision variables related to the amount of products to be produced and stored in the nodes of the SC, the flows of materials among the entities of the network, and shortfalls and excess at the customer centers are considered as second-stage variables. The methodology has been illustrated by solving an example. It was found that the proposed model yields more feasible and advantageous results.     

Taguchi method for analyzing the tactical planning model in a closed-loop supply chain considering remanufacturing option

Recent years, there has been a growing interest in reverse logistics, recycling, remanufacturing, and reusing due to the environmental concerns, economical issues, and legal obligations. Companies should take into account the recovery options such as recycling, remanufacturing, etc. while preparing their tactical plans. In this paper, a mixed integer linear programming model is proposed for tactical planning in a conceptual closed-loop supply chain with remanufacturing option. In the model, both forward and reverse flows are involved and two production alternatives are considered: either production of new products directly in manufacturing plants or bringing the returned products back to “as new condition” in the remanufacturing facilities. The proposed model attempts to optimize all of the consecutive stages in the closed-loop supply chain. Hence, the purpose of this research is to formulate a mathematical programming model to focus primarily on integrating remanufacturing as a recovery option into tactical planning process. The proposed model is applied to an illustrative case and solved by LINGO 9.0 optimization solver. In order to obtain the best objective function value that is targeted, the effects of the major factors regarding reverse flows and remanufacturing system are examined with the help of Taguchi experimental design technique at the end of the study. Analysis of variance, Taguchi's signal/noise ratios, analysis of means graphs and interaction graphs are provided by MINITAB 14 software and interpreted for the evaluation of experimental results and effects of related factors.     

[供应链调度]分时电价和时变行程时间下的供应链调度

针对单机供应链调度问题,在生产计划和批次配送阶段分别考虑分时电价政策和时变行程时间。以总成本最小为目标建立混合整数规划模型,通过对模型的分析给出了最优解的性质,以此将模型分解为若干个批次的机器调度子问题。对于子问题优化,设计了子集划分启发式算法并证明了算法的最优性。对于主问题的优化,设计了自适应变邻域搜索算法。数值计算结果验证了模型和算法的有效性,证明了供应链集成调度能减少大量的能源消耗。     

Cavitation effect on flow resistance of sleeve regulating valve

Sleeve regulating valve is the key component of the industrial system. As the main cause of vibration and noise inside the sleeve regulating valve, cavitation also increases the energy loss when fluid flows through the valve. In this paper, in order to quantitatively analyze the influence of cavitation in the sleeve regulating valve, the effects of throttling windows number, pressure difference, valve opening and flow direction on the resistance coefficient are investigated with the application of cavitation model. By defining the cavitation influencing factor of the resistance coefficient, the calculation formula of the resistance coefficient when cavitation occurs in the sleeve regulating valve is proposed. The results show that when the fluid flows forward and the aggravation degree of cavitation increases, the energy loss also increases. And in the backward flow, the effect of cavitation on the resistance coefficient is related to the valve opening and the throttling windows number. This work is of significance for the optimization and design of sleeve regulating valve and pipeline system.     

产品设计中的用户需求与产品质量特征映射方法研究

针对现代产品设计中将用户需求贯穿于产品开发全过程的基础问题展开研究,建立了用户需求与产品设计质量特征映射的理论模型,提出了由用户需求筛选与精化、产品质量特征获取与转换和产品质量特征优化与决策三个过程构成的映射方法。该方法采用网络分析法(ANP)确定用户需求和产品质量特征的重要度,建立了用户需求之间、产品质量特征之间、用户需求层与产品质量特征层之间的融合与冲突求解关系模型。在优化决策模型中,采用加权0-1目标规划法,综合考虑了成本、时间、现有资源和可行性等因素对产品质量特征的影响,实现了用户需求与产品质量特征的有效映射。并通过实例验证了该方法的有效性。     

Application of axiomatic design, TRIZ, and mixed integer programming to develop innovative designs: a locomotive ballast arrangement case study

In this paper, we present a method incorporating axiomatic design, TRIZ, and mixed integer programming (MIP) to solve engineering design problems. Axiomatic design decomposes the problem into several mutually independent sub-problems, TRIZ generates all feasible design concepts, and MIP optimizes cost and the numerical configuration among available design options. The method is illustrated on a locomotive ballast arrangement case study. Ballast arrangement is a key process for a locomotive assembly, which determines the carrying capacity. Due to the unsophisticated technology requirements, the ballast arrangement process has received little attention. The trend of mass customization, however, demands locomotive manufacturers to provide diverse products with affordable cost and reduced time. Thus, a flexible and easy to implement ballast arrangement process design is sought. The proposed method determines what material combinations, in what quantity, and where in the limited cavities should the ballast be allocated to minimize cost. Using the case study, we demonstrate the advantages in cost reduction and time savings. The synergy of these improvements not only can enhance productivity and agility but also competitive advantage.     

一种基于BSON技术的HMI软件组态格式兼容性设计方案

常规的文件格式在设计的时候,一般会考虑到兼容,性问题,设计上能做到向前兼容。同时,部分软件会提供另存为的功能,将文件保存为低版本的格式,以方便低版本软件识别。一些软件则通过分段式的数据存储,对文件内容进行划分,以提高文件的兼容性。也有的软件则通过一些数据区预留的方式,为后续的新增功能做准备。但是．这类方式都普遍存在灵活性低,维护成本大的缺点。本文以流程图组态文件为例．阐述了如何将BSON与组态文件的格式相结合,并实现文件前后版本互相兼容的方法。通过BSON的可遍历性的特点来解决文件的前后兼容问题,同时BSON本身灵活、高效的优点,使得我们在使用时能很方便的对文件进行解析操作。