Remanufacturing closed-loop supply chain network design based on genetic particle swarm optimization algorithm

As the huge computation and easily trapped local optimum in remanufacturing closed-loop supply chain network (RCSCN) design considered, a genetic particle swarm optimization algorithm was proposed. The total cost of closed-loop supply chain was selected as fitness function, and a unique and tidy coding mode was adopted in the proposed algorithm. Then, some mutation and crossover operators were introduced to achieve discrete optimization of RCSCN structure. The simulation results show that the proposed algorithm can gain global optimal solution with good convergent performance and rapidity. The computing speed is only 22.16 s, which is shorter than those of the other optimization algorithms.

Reliability supply chain network design model for perishable products

The classical supply chain network(SCN)design problem is extended,where the candidate facilities are subject to failure and the products are prone to elapsed time deteriorion.First,the reliable SCN design problem is defined by introducing the probability that a facility may be prone to inactivity based on the analysis of perishable product characteristics.The perishable product SCN design problem is formulated as a 0-1 integer programming model.The objective is to minimize the weighted sum of the operating cost(the fixed plus transportation cost)and the expected failure cost.And then,the perishable product SCN design model is discussed and solved using the genetic algorithm(GA).The results show how to generate the tradeoff curve between the operating costs and the expected failure costs.And these tradeoff curves demonstrate empirically that substantial improvements in reliability are often possible with minimal increase in the operating costs.

Literature Review on Network Design Problems in Closed Loop and Reverse Supply Chains

The productivity of an organization is very much affected by non-value adding activity like logistics, which moves the resources from suppliers to factory, raw materials/semi-finished items within the factory and finished goods from factory to customers via a designated distribution channel called as forward logistics. In some cases, parts of the products such as automobiles, computers, cameras, mobile phones, washing machines, refrigerators, garments, footwear and empty glass bottles of beverages, etc. will be brought back to the factories as a product recovery strategy through reverse logistics network which is integrated in a sustainable closed loop supply chain network. So, it is highly essential to optimize the movement of the items in the reverse logistics network. This paper gives a comprehensive review of literature of the design of networks for the reverse logistics as well as for the reverse logistics coupled with forward logistics. The contributions of the researchers are classified into nine categories based on the methods used to design the logistics network.

Closed-loop supply chain network equilibrium strategy model with environmental protection objectives

With the increasing popularity of ecological civilization and sustainable development,enterprises should consider environmental protection measures in their operations in addition to pursue their economic interests.This paper establsihes a closed-loop supply chain network model composed of multiple suppliers,manufacturers,retailers,recyclers,and demand markets—regarding their dual goals of the profit maximization and the minimization of carbon emissions.The conditions necessary for establishing overall equilibrium and an equilibrium model of the entire closed-loop supply chain network are determined by applying variational inequality and dual theory.A modified projection contraction algorithm is used to design a model-solving program.Finally,using numerical examples,the paper conducts a comparative static analysis on important parameters such as the weight coefficients of environmental protection objectives and consumers'awareness of low-carbon environmental protection and attains some beneficial enlightenment on management.The results indicate that when the environmental protection objectives of a certain type of enterprise increases,both the economic benefits and environmental protection performance will improve;when the environmental protection objectives of all enterprises increases simultaneously,environmental protection performance improves significantly,but the changes in economic benefits of different enterprises are inconsistent and profit coordination is more complex.Although consumers’awareness of low-carbon preference could improve environmental performance,it reduces the overall profits of network members and the entire closed-loop supply chain network as a whole.The above conclusions can be used as a reference for the government in designing low-carbon environmental protection policy and in closed-loop supply chain research.

Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain

This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.

Implementation of Hybrid Genetic Algorithm for CLSC Network Design Problem—A Case Study on Fashion Leather Goods Industry

The implementation of closed loop supply chain system is becoming essential for fashion leather products industry to ensure an economically sustainable business model and eco-friendly industrial practice as demanded by the environmental regulations, consumer awareness and the prevailing social consciousness. In this context, this research work addresses a closed loop supply chain network problem of fashion leather goods industry, with an objective of minimizing the total cost of the entire supply chain and also reducing the total waste from the end of life product returns. The research work commenced with a literature review on the reverse and closed loop supply chain network design problems of fashion and leather goods industry dealt in the past. Then, the identified CLSCND problem is solved using a mathematical model based on Mixed Integer Non-Linear Programme (MINLP) and then a suitable Hybrid Genetic Algorithm (HGA) developed for the CLSCND is implemented for obtaining optimum solution. Both the MINLP model and HGA are customized as per the CLSCND problem chosen and implemented for the industrial case of an Indian Fashion Leather Goods Industry. Finally, the solutions obtained for MINLP model in LINGO 15 and for HGA in VB.NET platform are compared and presented. The optimum solution obtained from the suitable HGA is illustrated as an optimum shipment pattern for the closed loop supply chain network design problem of the fashion leather goods industry case.

Designing a Reverse Logistics Network Model for Waste Batteries

The logistics industry plays an important role in circular economy.Therefore,not only economic benefits,but also environmental protection factors have to be considered in reverse logistics.This paper uses the multi-objective 0-1 mixed integer programming to establish a reverse logistics network optimization model for waste batteries.The objective function is to minimize both,logistics costs and carbon dioxide emissions.The model considers the basic settings of reverse logistics(including recycling nodes,manufacturing,and processing nodes)and the material flow between different settings.In solving the model,Lingo 14.0 is used in this paper.An actual case of a waste battery reverse logistics enterprise verifies the effectiveness of the model in this paper.The results show that the application of this model can effectively improve the operating efficiency of waste battery reverse logistics enterprises.

Supply chain network design under uncertainty with new insights from contracts

In this paper, the classical problem of supply chain network design is reconsidered to emphasize the role of contracts in uncertain environments. The supply chain addressed consists of four layers: suppliers, manufacturers, warehouses, and customers acting within a single period. The single owner of the manufacturing plants signs a contract with each of the suppliers to satisfy demand from downstream. Available contracts consist of long-term and option contracts, and unmet demand is satisfied by purchasing from the spot market. In this supply chain, customer demand, supplier capacity, plants and warehouses, transportation costs, and spot prices are uncertain. Two models are proposed here: a risk-neutral two-stage stochastic model and a risk-averse model that considers risk measures. A solution strategy based on sample average approximation is then proposed to handle large scale problems. Extensive computational studies prove the important role of contracts in the design process, especially a portfolio of contracts. For instance, we show that long-term contract alone has similar impacts to having no contracts, and that option contract alone gives inferior results to a combination of option and long-term contracts. We also show that the proposed solution methodology is able to obtain good quality solutions for large scale problems.

铁路工程建设可持续供应链网络集成优化研究

随着国家对铁路工程项目可持续发展的日益重视,迫切需要先进且集成的供应链网络设计方案理论与方法来提高供应链效率、可持续绩效以及资源利用率。实施可持续供应链网络设计已成为实现铁路工程可持续发展的重要途径,而供应商选择、物流设施选址、路径规划、库存管理以及工程废弃物回收再利用等决策是铁路工程供应链管理的核心与关键问题。针对我国铁路工程建设供应链管理特点,从可持续视角研究铁路工程建设供应链网络设计集成优化问题,提出两阶段的求解框架:其中,第1阶段基于可持续指标体系运用模糊TOPSIS方法确定最佳供应商选择;第2阶段针对物流设施选址、库存控制策略与网络最佳流量分配的集成决策问题,构建了基于模糊规划的多周期多目标供应链网络集成决策优化模型。该优化模型考虑了运输过程的不确定性,以供应链总成本、碳排放量最小以及社会效益最大为优化目标。针对上述多周期多目标优化模型的特征,设计了改进的宽容分层序列算法进行求解。最后,基于我国丰雄商铁路工程建设项目进行案例研究,验证了上述求解框架与算法的有效性,并针对单位运价、单位运输碳排放量以及弃置率3个关键参数进行了敏感性分析。研究结果表明:1)批量折扣策略可以在联合采购中节省大量成本;2)运输模式与路径优化对系统的效率和可持续绩效有决定性影响;3)与管理学手段相比,推进新能源的使用是降低碳排放量最有效的措施;4)社会效益的提高不可避免地需要更高的成本,政府合理的补贴政策是提高企业积极性的关键举措;5)长远来看,铁路工程项目中的废弃物回收利用是实现可持续工程建设的重要途径,其技术和应用的发展都应受到重视。

碳交易规制下基于生产工艺的可持续供应链网络设计研究

文中考虑生产工艺和碳排放对供应链网络设计的影响,使用混合整数线性规划的方法研究碳交易机制下生产工艺选择对可持续供应链网络设计的影响,分析不同生产工艺下供应链的各项成本及碳排放情况,讨论了不同生产工艺下的供应链各环节决策的变化.结果表明:采购成本占供应链运作成本比重最大,制造环节的碳排放占总碳排放的比重最大,采购环节和制造环节应该是供应链管理的重点关注对象,同时生产工艺选择也会影响供应链网络结构,在考虑碳排放因素的情况下解决了生产工艺变化对供应链网络的影响.

Closed-loop Supply Chain Based Battery Swapping and Charging System Operation: A Hierarchy Game Approach

To realize optimal day-ahead operation of battery swapping and charging systems(BSCSs),a closed loop supply chain(CLSC)based management scheme is proposed,where the game theory is adopted for benefits allocation.The CLSC is used to depict the battery-swapping-charging process between the battery charging stations(BCSs)and battery swapping stations(BSSs).The arrival,departure and swapping service of electric vehicles(EVs)at BSSs is modeled as distinct queues based on the network calculus theory.The depleted batteries(DBs)and well-charging batteries(WBs)based interaction among BCSs and BSSs is formulated as a Stackelberg game.In the game,one BCS acts as the leader and the BSSs act as the followers.The BCS sets optimized prices to maximize its utility and the BSSs optimally demand WBs,supply DBs and provide battery swapping services to maximize their own utilities while guaranteeing the quality of service(QoS)needed for battery swapping.The existence of Stackelberg equilibriums(SEs)of the proposed game is proved.A differential evaluation based hybrid algorithm is proposed to compute an SE.The effectiveness of proposed method has been demonstrated by the simulation results,guaranteeing the QoS and balancing benefits among the BCS and BSSs while maximizing social welfare.

基于协同优化算法的供应链网络设计与管理研究

文章探讨了基于协同优化算法的供应链网络设计与管理问题的解决方案。传统供应链网络设计面临路径规划、物流选址等挑战,文章在对这些问题进行深入分析的基础上,详细介绍了协同优化算法的基本原理,探讨了其在供应链管理中的潜在应用,提出了基于协同优化算法的供应链网络设计与管理模型,并详细描述了模型的构建过程和优化目标。通过仿真实验验证了协同优化算法在实际应用中的有效性和可行性,结果表明,该算法能够有效解决现实世界中的供应链管理问题,为提高供应链效率和降低成本提供有效的解决途径。

碳补贴政策下闭环供应链网络优化

在考虑碳排放和市场(运输价格、消费者需求和废旧品回收量)不确定的情况下,针对多层级、多产品的家电闭环供应链网络设计,建立包括生产商、分销商、消费者群以及回收中心和处置中心的网络规划模型。在政府针对使用低能耗产品的绿色消费者进行碳补贴的情况下,综合考虑闭环供应链总成本和总碳排放量的平衡,分析了不同补贴力度对消费者中绿色消费者比例浮动和整个闭环供应链网络规划设计的影响。通过算例证明了模型的有效性,为供应链网络设计者提供决策依据,并为政府针对消费者制定碳补贴政策实现减排的目的提供一定的理论依据。

基于本体与多Agent的可靠供应链网络设计模型

针对供应链环境下的分布性、不确定性和动态性特征,基于本体与多Agent技术,构建了一种集成多种智能算法的可靠供应链网络设计模型。通过服务本体实现成员企业服务发布与发现,通过工作流本体实现订单任务动态分解,综合采用投招标策略和可靠性优化策略,实现可靠供应链网络的最优设计。其中,优化Agent由投标企业可靠性评估机制、目标可靠性预测机制以及基于可靠性的任务分配机制构成。通过一个应用实例验证了系统的可行性与有效性。

基于不确定中断概率的鲁棒供应链网络设计

为了给决策者在不确定环境中设计具有鲁棒性的供应链网络提供决策支持,考虑供应链网络中上游制造商设备故障或网络中节点间链接失效导致的供应中断情况,建立了随机需求和供应中断下基于路径的供应链网络设计非线性规划模型。为解决非线性规划难以求解的问题,采用分段线性化方法将其转化为线性规划模型。进一步考虑了中断情景概率不确定的情况,并采用区间和椭球不确定集进行建模,给出了不确定中断概率下的供应链网络设计鲁棒优化模型;运用线性规划和拉格朗日对偶理论,将其转化为易于求解的线性规划和二阶锥规划问题。以实际案例为背景进行数值计算,验证了所建模型的有效性。

基于时间的随机需求二级分销网络物流系统集成优化研究

分销网络设计包括设施选址、库存控制、运输等方面的设计与优化,但以往只是从战略层、战术层、运作层来分别进行各自的研究。实际上,这三个层次的决策要素之间存在着复杂的互动关系,并存在着广泛的效益悖反关系,这些在变化的环境下显得尤为突出。本文充分考虑时间因素的重要性,从物流系统的集成优化高度出发,研究建立需求随机的多分销中心多顾客的设施选址———运输路线安排———库存控制问题(ILRIP)的模型,对此设计了一个两层粒子群优化(PSO)算法,并给出了计算实例。研究结果有助于供应链分销网络的集成优化,缩短商品流转周期,提高顾客服务水平,提升竞争力。

基于偏好与合作的供应链网络设计与集成优化

研究了集中与分散决策模式下的三级供应链网络设计与集成优化问题。为了体现决策者的偏好与合作行为,提出了考虑三类模糊算子的模糊多目标规划方法。分析了三类模糊算子对系统各个目标的隶属度、函数值以及供应链网络结构的影响。结果表明,加权的"极大极小"算子能够反映集中决策模式下核心决策者对各个目标的决策偏好,"模糊与"算子则能反映分散决策模式下各成员企业协调各个目标的合作意愿。为兼顾目标均衡与权重分配,提出了综合上述两个算子优点的修正"模糊与"算子。修正"模糊与"算子体现了集中决策和群体协商的管理思想,从而能够更好地提高决策效率。

求解农产品供应链网络设计问题的混合粒子群算法

为求解以混合整数规划(MIP)模型表征的农产品供应链网络(Agri-food Supply Chain Network,ASCN)优化设计问题,提出了基于混合粒子群算法(Particle Swarm Algorithm,PSA)的优化方法。分别将单邻域搜索和简化变邻域搜索作为局部搜索技术嵌入PSA中构建了两种混合PSAs。由混合PSA搜索MIP中二元决策变量,随后由LINGO求解MIP导出的线性规划问题并获取解。以陕西苹果产业集群的ASCN设计及其修改案例为例,验证了基于混合PSA优化方法的有效性。案例计算结果对比表明,增加局部搜索可显著增强PSA全局寻优能力,且简化变邻域搜索在改善PSA全局搜索能力上优于单邻域搜索。

再制造闭环供应链间竞争下的网络优化设计模型研究

将以往仅考虑成员企业间竞争的闭环供应链网络优化设计问题,扩展到考虑闭环供应链间竞争下的网络优化设计问题,网络中的运作成本不再局限于线性成本,而是处理非线性成本,且在网络优化设计中采用连续变量。基于再制造闭环供应链的关键功能活动构建再制造闭环供应链间竞争下的网络结构,基于功能活动弧段设计运作与回收成本和设计成本函数,利用均衡理论描述再制造闭环供应链间的竞争行为,利用变分不等式理论建立基于连续变量的再制造闭环供应链网络设计模型。利用提出的模型结合算例优化设计再制造闭环供应链网络,并分析再制造率对各条再制造闭环供应链销售额、运作与回收成本、设计成本和利润的影响,以及对各需求市场需求量、回收量和价格的影响。

采用优先权解码的多阶段供应链网络设计方法

建立基于物流成本最小的多级供应链网络模型。该模型综合考虑了运输成本,设施的建设开办成本以及生产装配成本,本质上属于混合整数非线性规划模型。由于非线性约束及供应链网络庞大的变量和约束条件,常规的分支定界法难以精确求解。为此,本文设计了基于优先权编码的遗传算法进行求解,并将求解结果与L ingo软件的算法结果进行比较,算例结果显示了这种算法的有效性。