回收率依赖回收产品质量的再制造EOQ模型

研究回收率依赖回收产品质量情况下制造/再制造混合系统的EOQ模型.该模型假设顾客的需求可通过新产品的制造和回收产品的再制造两种方式满足,且这两种产品无质量差异;需求率是确定的、连续的;总成本包括制造和再制造的固定启动成本,可销售产品和回收品的库存成本,以及缺货成本.当假设缺货成本无限大时给出不允许缺货情况下的模型.给出算例验证模型的有效性.     

选址-库存-路径问题模型及其集成优化算法

设施选址、库存控制和车辆路径安排是物流系统优化中的三个关键问题,三者之间存在相互依赖的关系,应该根据这种关系来相应地进行综合优化与管理物流活动。以典型的单一生产基地、单一产品、采用不断审查的(Q, r)库存策略的供应链二级分销网络为研究对象,建立了一个随机型选址-库存-路径问题优化模型;在将非线性混合整数规划转化为线性整数集合覆盖模型的基础上,采用列生成算法来获得一个近似最优解,再用分支定价法对初始解进行改进,以实现对整个问题“完全集成”的优化。最后,用随机生成的方式,产生了10至160个客户的计算实例,分析了运输费用和库存费用对总成本的影响,算法运算时间表明本文给出的算法能较快地求解这一复杂问题。     

再制造能力有限的多产品混合系统库存决策

为确定各产品的制造与再制造策略,对再制造能力有限的多产品混合系统进行研究.在系统中,对多种产品进行制造和再制造.每种产品在顾客使用后都会以恒定速率返回,但因再制造能力有限,有些产品无法用于再制造而被处置.每种产品需求恒定且由服务性产品来满足,服务性产品由制造品和再制造品组成,不允许缺货.在一次制造准备和至少一次再制造准备策略下构建了库存决策模型,利用拉格朗日乘数法和贪婪算法分别确定了各产品的再制造顺序和再制造比率.并当再制造比率一定时,给出了再制造准备次数为正整数时各产品制造与再制造策略的求解程序,得到了各产品制造和再制造批量、再制造准备次数等求解公式.最后,应用算例对模型及求解方法进行了验证.     

考虑退货情形下的闭环供应链双源库存控制策略

假设再制造闭环供应链由单个制造商和单个零售商组成,考虑制造商产品回收率、退货率和废旧产品再制造率的不确定性,建立再制造环节废旧产品的最优检测时间、购买时间和闭环供应链最低成本的数学模型.利用回收率、退货率和再制造率计算废旧产品的最优检测和购买的时间间隔,分析再制造环节中双源库存的成本最小化问题.研究表明:再制造环节可降低闭环供应链的双源库存成本,但随着回收率的增加,总成本先下降后增加;在回收率、退货率和再制造率三者共同作用下,最优检测和购买时间间隔的设置可降低双源库存成本,优化资源配置.     

马尔科夫决策过程在R/M系统库存控制中的应用

给出了有限阶段R/M(再制造/制造)系统集成库存模式,利用马尔科夫决策理论对库存容量有限、具有随机再制造零部件的R/M系统集成库存进行研究,考虑再制造零部件单位成本、新零部件可变费用和固定费用、超过库存容量的那部分再制造零部件的附加费用及有缺货赔偿的情况,给出了马尔科夫决策过程模型,得到了随机最优控制策略.     

带退货和软时间窗的多仓库选址-路径问题研究

选址-路径问题(location routing problems, LRP)是集成物流网络研究中的难题,也是任何一个大型物流配送企业必须面对的管理决策问题。本文在仓库容量约束和车辆容量约束的基础上,结合送取货一体化的配送模式和客户服务时间要求,建立了带退货和软时间窗的多仓库选址-路径(MDLRP)数学模型。针对MDLRP问题求解的复杂性,引入局部搜索算法和重组策略,设计了自适应混合遗传算法,对模型进行整体求解。最后进行数值实验,表明本文提出的模型和改进算法具有实用性和优越性,可为选址和车辆运输决策提供重要参考依据。     

需求率基于库存的变质物品的两货栈模型

针对需求受库存水平影响的变质品的两货栈系统,本文首先考虑了允许缺货但缺货要补情形下,分别给出了L₁系统(库存系统只用自己的货栈存放物品)和L₂系统(库存系统使用自己货栈和租用货栈存放物品)时,销售商的库存和运输策略模型。其次给出了允许缺货但缺货不补L₁系统和L₂系统时,销售商的库存和运输策略,并对模型最优解作了相关分析,最后给出算例,给销售商实际的库存管理提供了理论依据。     

考虑返回补偿策略的制造与再制造的最优决策

作为减少成本的一种有效方式,近年来,再制造获得了企业越来越多的关注.对于再制造企业,如何有效地返回产品是一个基本的问题,为此,考虑了一个返回补偿策略,即企业支付给愿意返回产品的消费者一个价格补偿.在这个策略下,回收数量是随机需求的一个比例.研究了一个两周期的库存系统,企业需要在每周期初决策新材料的采购数量以及分配给制造和再制造方式的生产数量.通过建立一个三级随机动态规划模型,给出了制造和再制造混合系统对于已实现需求的最优生产策略,同时证明了每个周期的目标函数对于库存补充数量是凸的,进而证明基本的库存策略仍然是最优的.最后从管理者的角度进行了数值分析.     

服务水平约束下双需求类静态配给策略

考虑一个周期盘点、无限期、缺货回补、双需求类的库存系统,其中高优先级需求的目标服务水平较高。系统采用基准库存策略补充库存,依据静态配给策略分配库存,即优先满足高优先级需求,仅当持有库存水平不低于固定配给阈值时满足低优先级需求。优化目标是在服务水平约束下最小化期望库存持有量。为提升计算效率,引入“预留库存假设”,即允许通过提高低优先级需求缺货水平的方式补充库存,使得期末持有库存水平不低于本期高优先级需求缺货水平与固定配给阈值之和。基于预留库存假设,给出两类需求服务水平和期望库存持有量的解析表达式,证明上述绩效指标关于控制参数的单调性,刻画满足服务水平约束的控制参数可行域,得到原系统最优控制参数的近似求解算法。算例分析表明,基于预留库存假设的绩效衡量方法和参数求解算法准确性好且计算效率高。     

销售率线性依赖瞬时库存水平的两货栈决策模型

在成熟期的存货影响销售环境下,考虑销售率线性依赖瞬时库存水平,不允许缺货,研究了一类非变质性物品的两货栈库存决策问题.建立了以系统平均总利润最大为目标的决策模型,分析了系统最优库存策略的存在性和唯一性,并给出了求解模型的有效方法.分析结果表明,库存管理者利用租用货栈进行订货决策时,除了要充分考虑企业自身的库存容量外,还取决于自有货栈产品相关参数对库存系统绩效的边际贡献率.     

A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods

Most of the research on integrated inventory and routing problems ignores the case when products are perishable. However, considering the integrated problem with perishable goods is crucial since any discrepancy between the routing and inventory cost can double down the risk of higher obsolescence costs due to the limited shelf-life of the products. In this paper, we consider a distribution problem involving a depot, a set of customers and a homogeneous fleet of capacitated vehicles. Perishable goods are transported from the depot to customers in such a way that out-of-stock situations never occur. The objective is to simultaneously determine the inventory and routing decisions over a given time horizon such that total transportation cost is minimized. We present a new “arc-based formulation” for the problem which is deemed more suitable for our new tabu search based approach for solving the problem. We perform a thorough sensitivity analysis for each of the tabu search parameters individually and use the obtained gaps to fine-tune the parameter values that are used in solving larger sized instances of the problem. We solve different sizes of randomly generated instances and compare the results obtained using the tabu search algorithm to those obtained by solving the problem using CPLEX and a recently published column generation algorithm. Our computational experiments demonstrate that the tabu search algorithm is capable of obtaining a near-optimal solution in less computational time than the time required to solve the problem to optimality using CPLEX, and outperforms the column generation algorithm for solving the “path flow formulation” of the problem in terms of solution quality in almost all of the considered instances.     

Solving the flight perturbation problem with meta heuristics

When there is a perturbation in a carefully constructed aircraft schedule, e.g. an aircraft breakdown, it is important to minimize the negative consequences of this disturbance. Here, a tabu search and a simulated annealing approach to the flight perturbation problem are presented. The heuristics use a tree-search algorithm to find new schedules for the aircraft, and utilize a path relinking strategy to explore paths between structurally different solutions. The computational results indicate that the solution strategies, especially the tabu search, can be successfully used to solve the flight perturbation problem.     

一种改进的禁忌搜索算法及其在选址问题中的应用

本文研究了选址问题中无容量限制的p-中值问题,在Rolland等人提出的有效禁忌搜索算法基础上,提出了一种以目标函数变化量作为评价函数的改进禁忌搜索算法,并进行了理论分析,然后将其与有效禁忌搜索算法作了性能比较.通过比较三个公共测试数据集的计算结果,验证了本文提出的禁忌搜索算法的可行性和有效性.     

Pricing used products for remanufacturing

Remanufacturing is one of recovery options for used products. As remanufacturing requires a continuous supply of used products, the economic incentive is required to attract customers to return their used products (called cores) and the problem of pricing a core becomes an important issue. Such a pricing problem is analogous to pricing an option, which can be used to sell the remanufactured cores (called core products). As sales price of core products follows a geometric Brownian motion, we propose a model here to evaluate the acquisition price of cores. This model links core acquisition price with the sale price of core product but assumes other costs such as logistics and remanufacturing to be deterministic. We have presented a numerical example to show its applicability. Since the model proposed here is generic, it is believed that the proposed model can be used in setting the core prices in many situations.     

A tabu search heuristic for ship routing and scheduling

The purpose of this paper is to solve a planning problem faced by many shipping companies dealing with the transport of bulk products. These shipping companies are committed to carrying some contract cargoes and will try to derive additional revenue from optional spot cargoes. An efficient tabu search algorithm has been developed to ensure quick decision support for the planners. The solutions generated by the tabu search heuristic are compared with those produced by a previously published multi-start local search heuristic. Computational results show that the tabu search heuristic yields optimal or near-optimal solutions to real-life instances within reasonable time. For large and tigthly constrained cases, the tabu search heuristic provides much better solutions than the multi-start local search heuristic. A version of the tabu search heuristic will be integrated as an improved solver in a prototype decision support system used by several shipping companies.     

竞争市场下考虑再制造产品售后服务的供应链运营策略

在同时生产新产品和再制造产品的原始制造企业(企业1)与生产具有替代性产品的企业(企业2)构成竞争关系下的供应链系统中,探讨供应链在不同售后服务策略下供应链的运营策略,分析在竞争市场下供应链定价策略和再制造产品的售后服务对定价策略及供应链中各企业利润的影响。揭示再制造产品售后服务对定价策略和供应链各企业最优利润的影响。得到如下主要研究结论:(1)当制造企业为再制造产品提供售后服务时,再制造产品销售量增加,新产品和竞争替代产品销售量降低;有趣的是新产品和再制造产品的市场零售价格同时增加,竞争替代产品的市场零售价格降低。(2)制造企业为再制造产品提供售后服务时的利润总是大于没有售后服务时的利润,且不受单位产品生产成本影响。同时当单位产品生产成本较高时,制造企业为再制造产品提供售后服务策略会带来竞争对手企业利润增加。这些结论对具有再制造产品供应链如何提供再制造产品售后服务具有一定指导作用和管理启示。     

Multi-objective tabu search using a multinomial probability mass function

A tabu search approach to solve multi-objective combinatorial optimization problems is developed in this paper. This procedure selects an objective to become active for a given iteration with a multinomial probability mass function. The selection step eliminates two major problems of simple multi-objective methods, a priori weighting and scaling of objectives. Comparison of results on an NP-hard combinatorial problem with a previously published multi-objective tabu search approach and with a deterministic version of this approach shows that the multinomial approach is effective, tractable and flexible.     

Solving a manpower scheduling problem for airline catering using metaheuristics

We study a manpower scheduling problem with job time windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off. Jobs (flights) must be serviced within a given time-window by a team consisting of a driver and loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams and assign teams and start-times for the jobs, so as to service as many flights as possible. Only teams with the appropriate skills can be assigned to a flight. Workload balance among the teams is also a consideration. We present model formulations and investigate a tabu search heuristic and a simulated annealing heuristic approach to solve the problem. Computational experiments show that the tabu search approach outperforms the simulated annealing approach, and is capable of finding good solutions.     

An introduction to population approaches for optimization and hierarchical objective functions: A discussion on the role of tabu search

Population approaches suitable for global combinatorial optimization are discussed in this paper. They are composed of a number of distinguishable individuals called "agents", each one using a particular optimization strategy. Periods of independent search follow phases on which the population is restarted from new configurations. Due to its intrinsic parallelism and the asynchronicity of the method, it is particularly suitable for parallel computers. Results on two test problems are presented in this paper. The individual search optimization strategies for each agent have been chosen having the basic characteristics of tabu search. This has been done in order to avoid mixing the hypothesized properties of these population approaches with those of more elaborate tabu search strategies, but remarking on its main characteristics. A set of four test problem "landscapes" is discussed and their use to improve and benchmark the results by using tabu search as the individual optimization strategy within a population heuristic is suggested and explored. The application of tabu search to new problem areas, like molecular biology, is also investigated.     

A Hybrid Meta-Heuristic for the Batching Problem in Just-In-Time Flow Shops

This paper is concerned with a batching problem encountered in the context of production smoothing in just-in-time manufacturing systems. The manufacturing system of interest is a multi-level system with a flow-shop at the final level. We develop a hybrid meta-heuristic method to solve the batching problem, which is known to be NP-hard. We hybridize strategic oscillation (SO) and path re-linking (PR) methods and compare the hybrid method's performance to two benchmark methods: a bounded dynamic programming method developed for the problem earlier and an implementation of robust tabu search (RTS) meta-heuristic. Through a computational study, we show that the proposed hybrid method is effective in solving the problem within several minutes of computer time and yielding near-optimal results.