钢铁工业三级供应链协调生产计划研究

为了研究矿山、选矿厂和炼铁厂所构成的钢铁工业三级供应链中的协调生产计划问题，建立了相应的混合整数非线性规划模型。该模型的特点是：①集成3个环节的生产计划；②集成生产与运输计划。针对该模型的特殊结构，提出了一种将原问题转化为等价的多个线性规划问题，然后使用Excel标准线性规划程序求解的策略。最后，通过案例说明了模型的有效性，并探讨了进一步研究的方向。     

基于随机需求的多级供应链网络优化模型的研究

通过对多产品、多级供应链网络的分析,提出了一种基于随机需求的多级供应链网络的优化模型。采用非线性混合整数数学规划方法,得到的供应链成本最小。针对在供应链中需求的多变性,应用反馈控制器来维持所有节点的产品库存,以此达到供应链的稳定。最后,应用仿真分析了反馈控制器对降低不稳定性的效果。     

Reverse logistics network design using simulated annealing

Reverse logistics is becoming more important in overall industry area because of the environmental and business factors. Planning and implementing a suitable reverse logistics network could bring more profit, customer satisfaction, and a nice social picture for companies. But, most of logistics networks are not equipped to handle the return products in reverse channels. This paper proposes a mixed integer linear programming model to minimize the transportation and fixed opening costs in a multistage reverse logistics network. Since such network design problems belong to the class of NP-hard problems, we apply a simulated annealing (SA) algorithm with special neighborhood search mechanisms to find the near optimal solution. We also compare the associated numerical results through exact solutions in a set of problems to present the high-quality performance of the applied SA algorithm.     

A novel hybrid method for supply chain optimization with capacity constraint and shipping option

In a modern market, supply chain network design is considered as a strategic decision that provides the proper platform for cost management and increases the competitive edge of enterprise. In a five-tier supply chain, there are several facilities such as suppliers, manufacturers, warehouses, distribution centers, and retailers or customers. For product transportation from one facility to another, different types of options may be used. These options have variety price and the manager should do the best assignment to reduce the total cost. In this paper, we formulated an integer programming model for a five-tier supply chain with capacitated facility and multiple transportation option with fixed lead time. We also proposed a novel meta-heuristic solution methodology that combines the Taguchi's feature with artificial immune approach in order to solve the proposed model. The performance of the proposed solution methodology has been examined against a set of numeric instances and the obtained results are compared with those provided by hybrid genetic algorithm and Taguchi and artificial immune system. Results indicate that this methodology can make better results than previous solutions effectively.     

基于禁忌搜索的平行机多工厂供应链调度

提出一类平行机多工厂供应链调度问题,从整体的角度优化订单分配、生产调度和运输调度。以交货期限内完成所有工件的生产和运输总成本最小化为目标,构建了问题的混合整数规划模型。设计了一种基于向量组编码结构的禁忌搜索算法以求解该问题。使用供应链调度策略和独立决策策略分别对算例进行求解,数据结果验证了供应链调度策略的优越性。禁忌搜索算法结果与CPLEX的求解结果对比表明,禁忌搜索算法有效可行。     

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.     

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。     

[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。     

面向供应链的高级计划与排程的混合整数规划模型

针对面向供应链的高级计划与排程问题,提出了一种混合整数规划模型。该模型是在考虑供应链物理约束、机器能力约束、工件加工顺序约束、可选机器、订单交付期的基础上,以最小化提前/拖期惩罚为目标而构建起来的。算例分析表明,该模型能够得出最优生产排程。     

Supply chain focus dependent safety stock placement

Increasing globalization, growing product range diversity, and rising consumer awareness are making markets highly competitive, forcing supply chains to adapt constantly to different stimuli. Growing competition between supply chains (as well as players within them) is also warranting a priority for overall supply chain performance over the goals of individual players. It is now well established in the literature that, among the many order winners, both overall supply chain cost and responsiveness (i.e., supply chain lead time) are the most significant determinants of supply chain competitiveness. The literature, however, mostly focuses on supply chain cost minimization with rather simplistic treatment of responsiveness. By introducing the concept of a coefficient of inverse responsiveness (CIR), we facilitate efficient introduction of responsiveness related costs into the scheme of supply chain (SC) performance evaluation and/or optimization. Thus, our model aids supply chain managers in achieving better strategic fit between individual business unit strategies and overall supply chain requirements in terms of cost efficiency and responsiveness. In particular, it aids in strategic placement of safety stocks at different stages in the supply chain. Our model also offers managerial insights that help improve our intuitions into supply chain dynamics. The model is more suited for strategic SC alignment, for example, when dealing with product changeovers or introduction of new product, rather than for operational control.     

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.     

The right time and place [strategic positioning and competitive space]

Increasingly in the UK, companies that have traditionally considered themselves as manufacturers are being advised to now see themselves as service providers and to reconsider whether to have any production capability. A key challenge is to translate this strategy into a selection of product and service-centred activities within the company's supply chain networks. Strategic positioning is concerned with the choice of business activities a company carries out itself, compared to those provided by suppliers, partners, distributors and even customers. In practice, strategic positioning is directly impacted by such decisions as outsourcing, off-shoring, partnering, technology innovation, acquisition and exploitation. If companies can better understand their strategic positioning, they can make more informed decisions about the adoption of alternative manufacturing and supply chain activities. Similarly, they are more likely to reject those that, like off-shoring, are currently en vogue but are highly likely to erode competitive edge and business success. Our research has developed a new concept we call 'competitive space' as a means of appreciating the strategic positioning of companies, along with a structured decision process for managing competitive space. Our ideas about competitive space, along with the decision process itself, have been developed and tested on a range of manufacturers. As more and more manufacturers are encouraged to move towards system integration and a serviceable business model, the challenge is to identify the appropriate strategic position for their organisations, or in other words, to identify their optimum competitive space for manufacture.     

Manufacturing supply chain design and evaluation

Successful supply chain management calls for robust supply chain design and evaluation tools. Many published papers focused on high level strategic aspects of supply chain design and the results are usually generic guidelines for business executives rather than specific tools for plant managers. In this paper, we present a decision-based methodology for supply chain design that a plant manager can use to select suppliers. The methodology utilizes the techniques of analytic hierarchy process and preemptive goal programming. Supply chain operations reference model level I performance metrics are incorporated into the methodology as the decision criteria. In addition, a set of performance metrics is developed to evaluate the overall supply chain effectiveness, which allows direct comparison of different supply chain designs.     

Designing a stochastic distribution network model under risk

In this paper, we present a stochastic supply chain network model under risk, in which three tiers of decision makers of suppliers, distribution centers (DCs), and customers seek to determine their optimal plans. Unlike other studies in the extant literature, we use financial risk measure to model and for the first time, a new methodology based on finance literature is used to optimize the conditional value-at-risk (CVaR) measure for the problem. In fact the aim of this paper is to show the benefits of considering CVaR to control the risks in the supply chain networks. Also in order to obtain the economics of scale, a piecewise linear transportation cost function is applied between suppliers and DCs. We formulate the problem as a convex mixed integer program. A two-phase (constructive and improvement) heuristic method is developed to solve the problem. In the constructive phase, an initial solution is built randomly, and in improvement phase, this solution is improved iteratively by using a hybrid algorithm combining Tabu search and simulated annealing methods. Numerical experiments demonstrate the practicability of considering CVaR in the model which is promising in the supply chain network area, and also the significant efficiency of the heuristic method in terms of CPU times.     

Integrated supply chain design using multi-criteria optimization

Supply chain management (SCM) presents significant opportunities for improving profit margins and reducing cost. It encompasses functional and geographical integration as well as integration of tactical and operational decisions. The functional integration aspects involve purchasing, manufacturing, and logistics within the company and across the supply chain. A supply chain design framework has been developed including linear/mixed integer multi-criteria optimization models for determining the identified supply chain design parameters. The selection of suppliers, determination of production quantities, inventory locations and sizes, selection of transportation method and transported quantities in a multi-stage, multi-level supply chain are investigated. Additional criteria including first-time quality (FTQ) and suppliers on-time delivery risk with and without allowing splitting of customer demand between suppliers are considered. An example of typical automotive power train supply chain design and decision issues is used to illustrate the effect of various factors.     

A fuzzy multi-objective programming model for supplier selection with volume discount and risk criteria

In contemporary supply chain management, the performance of potential suppliers is evaluated against multiple criteria. In this paper, a fuzzy multi-objective programming model is outlined to propose supplier selection taking quantitative, qualitative, and risk factors into consideration. Also quantity discount has been considered to determine the best suppliers and to place the optimal order quantities among them. The mixed integer derivative nonlinear programming is obtained from fuzzy multi-objective programming model by chance-constrained method. To solve this problem, an innovative method is proposed. In addition, several “what if” scenarios are facilitated. Finally, a real-life sample is used to validate the proposed model.     

多目标追逐问题的一种混合整数线性规划解

研究多车辆多目标追逐的路径规划问题。提出两个基于混合整数线性规划 (Mixed integer linear programming, MILP) 的多目标追逐 (Multi-target pursuit, MTP) 模型：就近追逐和“一对一”使能追逐。在两个MIP追逐模型中,小车运动的状态方程考虑为具有线性阻尼的质点动力学方程。采用整数变量描述小车与障碍物的相对位置信息,提出 “目标膨胀尺寸”的概念来描述对目标的追逐,定义小车的“追逐方向”。采用选取整变量的等高面法求解MILP追逐问题,并给出初始内点整变量的确定方法。最后给出仿真试验1对两个多目标追逐模型进行对比研究,仿真试验2证实了算法的效率。     

租赁车辆运输外包模式下多次直接运输策略的集成库存运输计划

分销网络在车辆租赁运输外包模式下,如何协调同步库存和运输计划是需要确定的运作决策.为此,讨论了多产品、单分销商、多用户的分销网络中,分销中心在租赁车辆外包模式和多次直接运输策略下的配送计划问题,建立了该问题的混合整数规划模型MTDS-ⅡT.根据问题的特点,设计并开发了基于部分链的遗传算法,以求解该模型.     

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.     

Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming

A closed-loop supply chain (CLSC) network is composed of both forward and reverse flows. An essential issue to be considered in designing any supply chain network is determination of number and locations of facilities in each layer of the network. Such a problem is a challenging job, since it contains sub-problems which are proven to be nondeterministic polynomial time complete. This paper proposes a CLSC distribution network design problem in which reverse flows are imported into forward model proposed by Selim and Ozkarahan (Int J Adv Manuf Technol 36:401–418, 1). Such a model is considered assuming forward covering (model I) and backward covering (model II) objectives, and then results are compared against the model incorporating covering of both forward and backward networks (model III). Our aim is to accentuate on the role of considering backward parameters in design of a CLSC network and to show how results differ from considering sub-problems separately. To model and solve the problem, a fuzzy goal programming approach is developed for network design in an interactive manner between decision maker and the model. To validate the presented model and the proposed solution approach, a test problem is presented and comparison of results is made using this problem. The results show that the proposed model can solve the CLSC problems in a manageable time. Moreover, outputs of the three models differ significantly. Therefore, the role of incorporating backward flows into the network design problem has been shown using our experiments.