基于批量流的多阶段生产系统的优化问题研究

考虑一个多阶段生产系统,在每个阶段上生产批量被分成若干个子批量进行加工,子批量可以相等也可以不相等,同时每个阶段上在相邻子批量之间可以有空闲。每个阶段上子批量的数目可以不相等。文中首先以系统总变动成本为目标函数对这样一个系统建立对应的模型,提出了求解这一问题的启发式方法,通过数值算例验证了这一方法的有效性。此外,还讨论了重启成本、空闲成本和对应于子批量的调整成本对系统总变动成本、生产批量以及子批量数目的影响。     

一种有限信息共享的全局寻优供应链双边协同计划方法

针对有限信息共享条件下,供应链协同计划难以实现计划调整的收敛性和达到全局最优的问题,提出一种具有多点搜索舜口概率搜索特征的协同计划方法.将协商中交流的备选计划及其所产生的成本变化信息融入到计划调整算法中.以遗传算法的选择、交叉和变异过程为调整机制,将算法的迭代过程与计划协商过程结合在一起.在确定上下游企业能力约束多产品批量计划模型和最小累积需求求解方法及其模型的基础上,分析了协同计划过程中的编码、适应度函数、初始计划组生成和选择、交叉、变异算法等主要要素,并给出协同计划流程.通过仿真实验验证了该方法的有效性和相对的优越性.     

多销售点生产──库存系统协调控制模型与算法

本文研究一个有多个销售点的生产企业的生产库存协调控制问题。生产企业将按费用最低的要求来确定生产批量；而销售点则按利润目标来确定其最优订购批量；它们之间的总量不衡将由生产企业通过价格折扣方式来协调,即鼓励销售商采取满意的订购批量,使销售商也能实现利润最大化。文中研究了如何确定最优生产批量、销售商的订购批量和合理的价格折扣等问题,建立了数学模型,给出了相应的算法,并讨论了需求随价格弹性变动情形下生产一库存一销售系统协调控制的问题,得到了一些新的结果。     

需求替代的两产品动态批量最优预测时阈研究

研究了存在需求单向替代的两产品动态批量决策的最优预测时阈问题.构建了包含替代成本、生产转换成本和库存成本在内的成本最小化模型,分析得出在只存在3类再生点(Ⅰ类、Ⅱ类和Ⅲ类)情形下的再生点单调性特征.同时,设计出了多项式时间的前向动态规划算法.运用数值试验分析了最优预测时阈与生产转换成本、替代成本、需求特征(需求增长性和...     

经济批量排产问题的一种排产方法

针对经济批量排产问题假定生产可以在库存降为0之前开始,并且提出新的算法求产品的生产顺序。结果表明,该排产方法成本要低于其他2种常用的经济批量排产问题的方法,并且给出了算法的时间复杂性。     

考虑故障停机的生产控制与维修计划联合决策模型

通过生产控制与维修计划协同决策,降低生产成本。首先描述生产过程,分析各项费用。其次,建立了考虑生产过程失控、故障率和故障停时间的生产过程控制、生产计划优化和维修管理联合优化决策的模型。通过模型求解,联合制定出生产过程检查策略、生产计划（经济生产批量、生产批次）以及维修计划（PM间隔期）,实现单位时间内总费用最低的目标。再次,案例研究,分析生产过程失控、故障率和故障停机时间对于经济生产批量、生产过程检查策略和生产系统维修计划的影响。该模型从理论上解决了生产过程控制、生产计划优化和维修管理联合优化决策难题,对于指导企业制定生产计划和生产系统的检修计划,进而提高产品质量、降低生产成本、确保准时交货都具有指导意义和实用价值。     

炼钢热轧一体化生产与物流计划模型及求解

合理的板坯与热轧卷库存、缩短产品的生产周期、降低能源消耗、按合同交货以提高客户满意度已成为钢铁生产管理的要求.为了降低生产与物流成本,本文针对炼钢与热轧生产及其衔接方式的特点,考虑能力和两个阶段冲突约束条件下构建生产与物流计划层次的一体化模型.分析了无能力约束和允许延迟条件下热轧批量的极点特征,对原问题采用Dantzi...     

基于遗传算法的生产批量优化问题

针对生产费用、生产准备费用和库存费用综合指标最小的、最优的能力约束生产批量问题,建立基于遗传算法的数学模型,通过模拟试验及实际问题计算,验证算法的可行性。     

基于投产点库存的随机综合生产计划模型研究

以企业基于投产点法的生产与库存控制策略为研究起点,分析了随机需求条件下生产系统服务水平与库存水平的数量关系,并将产品在计划期间的平均库存量引入综合生产计划模型。模型中计划期产量是与产品需求具有相同分布的随机变量,模型的优化目标是通过确定最佳的投产库存量和生产系统服务水平,求得相应的计划期产量区间。提出了模型的计算机辅助求解算法,并采用案例分析验证了模型的有效性。     

库存共享和服务水平限制下三级分销网络侧向转运模型与算法

侧向转运是库存共享的一种方式,一方面会减少库存成本,另一方面又会因转运而增加运输成本,针对这一问题考虑不同时间窗W^k的服务水平产生的服务水平的分级,构建三级分销网络中基于库存共享与时间服务水平限制的批量订货模型,分销网络模型中包含一个制造商、一个RDC、m个DC、n个客户。其中客户的需求相互独立且服从泊松分布,DC的订货提前期服从指数分布。首先,建立了基于时间服务水平限制的分销网络系统总成本最小化模型,并将再购点、订购批量等库存参数作为同时作为决策变量,以达到三级备件分销网络的成本优化;其次,根据问题和模型的特点对所建的模型开发了基于采用贪婪增加算法的求解思想求解问题,以便给管理者提供决策参考并通过降低利润的方式增加效益和资源利用率;最后,通过中航材集团推行的“航材共享”项目作为算例分析,将三个分销区域与机场群组成的备件分销系统进行建模分析,验证了本文模型的有效性,成本优化的显著性。研究结果表明,三级分销网络中,RDC采用连续盘点的（Q,R）补货策略、DC采用（Q,R,H）的补货策略时系统总成本与普遍采用的定期盘点策略和连续盘点中的One-for-One订货策略成本相比,DC之间的库存共享策略能有效降低整个系统的成本,例如,在案例研究中发现成本降低约为30%。     

PRODUCTION SCHEDULING OF CONTINUOUS FLOW LINES: MULTIPLE PRODUCTS WITH SETUP TIMES AND COSTS

The problem of production planning and setup scheduling of multiple products on a single facility is studied in this paper. The facility can only produce one product at a time. A setup is required when the production switches from one type of product to another. Both setup times and setup costs are considered. The objective is to determine the setup schedule and production rate for each product that minimize the average total costs, which include the inventory, backlog, and setup costs. Under the assumption of a constant production rate, we obtain the optimal cyclic rotation schedule for the multiple products system. Besides the decision variables studied in the classical economic lot scheduling problem (ELSP), the production rate is also a decision variable in our model. We prove that our solutions improve the results of the classical ELSP.     

Optimizing multi-stage production with constant lot size and varying number of unequal sized batches

This paper describes a model for a multi-stage production/inventory system in which a uniform lot size is produced through all stages with a single setup and without interruption at each stage. Partial lots, called batches, may be transported to the next stage upon completion. The number of the unequal sized batches may differ across stages. Considering setup costs, inventory holding costs, and transportation costs, an optimization method is developed to determine the economic lot size and the optimal batch sizes for each stage. The method is illustrated by a computational example and further numerical simulations.     

Setups and effective capacity: the impact of lot sizing techniques in an MRP environment

This study investigates how lot sizing techniques influence the profit performance, inventory level, and order lardiness of an assembly job shop controlled by MRP. Four single-level lot sizing techniques are compared by simulation analysis under two levels of master schedule instability and two levels of end item demand. A second analysis investigates the influence of a multilevel lot sizing technique, the generalized constrained-K (GCK) cost modification, on the four single-level techniques at low demand and low nervousness. The analyses reveal a previously unreported phenomenon. Given the same inventory costs, the single-level lot sizing techniques generate substantially different average batch sizes. The lot sizing techniques maintain the following order of increasing average batch size (and decreasing total setup time):

economic order quantity (EOQ)

period order quantity (POQ)

least total cost (LTC)

Silver-Meal heuristic (SML)

The causes for different average batch sizes among the lot sizing techniques are analysed and explained. Demand lumpiness, inherent in multilevel manufacturing systems controlled by MRP, is found to be a major factor. The number of setups each lot sizing technique generates is the primary determinant of profit performance, inventory level, and order tardiness. EOQ, a fixed order quantity technique, is less sensitive to nervousness than the discrete lot sizing techniques. EOQ_, however, generates the smallest average batch size, and, therefore, the most setups. Since setups consume capacity, EOQ, is more sensitive to higher demand. SML generates the largest average batch sizes, and is, therefore, less sensitive to increased demand. At low demand, the other lot sizing techniques perform better on all criteria. They generate smaller batches and, therefore, shorter actual lead times. The GCK cost modification increases the average batch size generated by each lot sizing technique. GCK improves the profit and customer service level of EOQ the lot sizing technique with the smallest batches. GCK causes the other lot sizing techniques to generate excessively large batches and, therefore, excessively long actual lead times.     

考虑交货因素的热轧无缝钢管订单排程模型与算法

无缝钢管的市场需求具有多品种、小批量的特点，为了在满足客户需求的同时保证高效连续化生产，文章在满足生产工艺特征的基础上将配送地址和交货期等合同因素引入热轧无缝钢管订单排程问题中，建立了以适期交货、订单集中生产配送和最小化机器设备调整为优化目标的订单排程优化模型，并设计了两阶段求解算法：首先，以订单交货期与配送地址差异最小为目标，基于凝聚策略设计了订单聚类算法，将具有相同工艺约束、相似合同要求的订单进行聚类，并形成初始轧制计划；然后，以设备调整和提前/拖期最小为目标，设计混合变邻域搜索算法，对初始轧制批次进行排程优化。基于实际订单数据的实验结果表明，模型和算法对问题的描述和求解是可行有效的。     

Stabilized‐Cycle Strategy for Capacitated Lot Sizing with Multiple Products: Fill‐Rate Constraints in Rolling Schedules

In practice, deterministic, multi‐period lot‐sizing models are implemented in rolling schedules since this allows the revision of decisions beyond the frozen horizon. Thus, rolling schedules are able to take realizations and updated forecasts of uncertain data (e.g., customer demands) into account. Furthermore, it is common to hold safety stocks to ensure given service levels (e.g., fill rate). As we will show, this approach, implemented in rolling schedules, often results in increased setup and holding costs while (over‐)accomplishing given fill rates. A well‐known alternative to deterministic planning models are stochastic, static, multi‐period planning models used in the static uncertainty strategy, which results in stable plans. However, these models have a lack of flexibility to react to the realization of uncertain data. As a result, actual costs may differ widely from planned costs, and downside deviations of actual fill rates from those given are very high. We propose a new strategy, namely the stabilized cycle. This combines and expands upon ideas from the literature for minimizing setup and holding costs in rolling schedules, while controlling actual product‐specific fill rates for a finite reporting period. A computational study with a multi‐item capacitated medium‐term production planning model has been executed in rolling schedules. On the one hand, it demonstrates that the stabilized‐cycle strategy yields a good compromise between costs and downside deviations. Furthermore, the stabilized‐cycle strategy weakly dominates the order‐based strategy for both constant and seasonal demands.     

Simultaneous determination of production lot size and process parameters under process deterioration and process breakdown

The purpose of this study is to combine production-inventory management with process-quality design for determining production lot size and process parameters under the possibility of process deterioration and breakdown. The total cost of such an integrated model includes: the combined setup cost (production setup and process resetting), the costs of quality loss, tolerance and mean costs for processes established, a penalty cost for process breakdown and carrying costs for cumulated inventory. The quadratic quality loss function is introduced to assess quality loss within the system. Decision variables include the initial setting (process mean) and process tolerance for process parameters determination, and production lot size for production-inventory management. The cycle time for production-inventory management is assumed to be the same as the resetting cycle for the new process-quality system. The contribution of this study lies in its development of an integrated model that enables process parameters, production lot size, and cycle time to be determined concurrently for quality and economic considerations, and at an earlier time in the process design and production management stage. An example is presented to demonstrate the proposed model.     

WIP inventories in the simultaneous determination of optimal production and purchase lot sizes

This paper studies an integrated production and purchasing lot sizing model with work-in-process WIP inventory. In this model, the single product is made in a multiprocess manufacturing system. The raw materials are procured from outside sources and are converted gradually into the product. A solution procedure is developed to simultaneously find the optimal lot sizes for the product and its raw materials and the corresponding total relevant cost. It is shown that if the cost of WIP inventory is considered in the production lot size computation, the optimal lot sizes of the product as well as those of the raw materials could be altered significantly.     

Optimum common cycle for scheduling a single-machine multiproduct system with a budgetary constraint

This paper deals with the single machine multi-product lot size scheduling problem, and has two objectives. The first objective is to minimize the maximum aggregate inventory for the common cycle (CC) scheduling policy. A simple and easy-to-apply rule has been developed which determines the optimal production sequence that achieves this objective. The second objective is to find an optimal common cycle for minimizing the average production and inventory costs per unit time, subject to a given budgetary constraint. A method has been presented that achieves this objective     

Economic Production Lot Sizing with Periodic Costs and Overtime*

Traditional approaches for modeling economic production lot‐sizing problems assume that a single, fixed equipment setup cost is incurred each time a product is run, regardless of the quantity manufactured. This permits multiple days of production from one production setup. In this paper, we extend the model to consider additional fixed charges, such as cleanup or inspection costs, that are associated with each time period's production. This manufacturing cost structure is common in the food, chemical, and pharmaceutical industries, where process equipment must be sanitized between item changeovers and at the end of each day's production. We propose two mathematical problem formulations and optimization algorithms. The models' unique features include regular time production constraints, a fixed charge for each time period's production, and the availability of overtime production capacity. Experimental results indicate the conditions under which our algorithms' performance is superior to traditional approaches. We also test the procedures on a set of lot‐sizing problems facing a national food processor and document their potential economic benefit.     

Effect of forecast errors on rolling horizon master production schedule cost performance for various replanning intervals

Master production schedules are usually updated by the use of a rolling schedule. Previous studies on rolling schedules seem to form the consensus that frequent replanning of a master production schedule (MPS) can increase costs and schedule instability. Building on previous research on rolling schedules, this study addresses the impact of overestimation or underestimation of demand on the rolling horizon MPS cost performance for various replanning frequencies. The MPS model developed in this paper is based on actual data collected from a paint company. Results indicate that under both the forecast errors conditions investigated in this study, a two-replanning interval provided the best MPS cost performance for this company environment. However, results from the sensitivity analysis performed on the MPS model indicate that when the setup and inventory carrying costs are high, a 1-month replanning frequency (frequent replanning) seems more appropriate for both of the above forecast error scenarios.