An integrated distribution routing model in multi-supply center system

A distribution routing problem with time constraint is one of the important problems in distribution and supply center management. This research is concerned with an integrated distribution routing problem for multi-supply centers based on improved genetic algorithm and graphical user interface (GUI)-type programming. In this research, we proposed a method based on a three-step approach: in step 1 a sector clustering model is developed to transfer the multi-supply center problem to single supply center problems which are easier to be solved; in step 2 we developed a vehicle routing model with time constraints and in step 3 we developed a GA-TSP model which can improve the vehicle routing schedules. The objective of the problem is to minimize the logistic cost for a set of customers without being tardy or exceeding the capacity or travel time of the vehicles. For computational purpose, we developed a GUI-type computer program according to the proposed methods and the sample outputs show that the proposed method is very effective on a set of standard test problems, and it could be potentially useful in solving the distribution routing problems.     

A multiple ant colony optimization algorithm for the capacitated location routing problem

The success of a logistics system may depend on the decisions of the depot locations and vehicle routings. The location routing problem (LRP) simultaneously tackles both location and routing decisions to minimize the total system cost. In this paper a multiple ant colony optimization algorithm (MACO) is developed to solve the LRP with capacity constraints (CLRP) on depots and routes. We decompose the CLRP into facility location problem (FLP) and multiple depot vehicle routing problem (MDVRP), where the latter one is treated as a sub problem within the first problem. The MACO algorithm applies a hierarchical ant colony structure that is designed to optimize different subproblems: location selection, customer assignment, and vehicle routing problem, in which the last two are the decisions for the MDVRP. Cooperation between colonies is performed by exchanging information through pheromone updating between the location selection and customer assignment. The proposed algorithm is evaluated on four different sets of benchmark instances and compared with other algorithms from the literature. The computational results indicate that MACO is competitive with other well-known algorithms, being able to obtain numerous new best solutions.     

Green logistics at Eroski: A case study

In today’s highly competitive environment, green logistics issues are gaining interest. This paper analyses how logistics managers could lead the initiative in this area by incorporating environmental management principles into their daily decision-making process. A case study is given to show how they can turn practices into green while simultaneously meet the efficiency objectives. We have chosen one of the leader companies of the Spanish food distribution sector to check this hypothesis. The study covers the introduction of several changes into its fleet management and the implementation of a methodology to solve vehicle routing problems with environmental criteria minimisation.     

某物流配送中心运输车辆噪声对居民的影响

一些企业在生产过程中排放的噪声级较高,干扰了周围居民的正常生活,导致居民对噪声污染的投诉越来越多。为了明确某企业噪声对周围居民区的影响范围和程度,通过测定某物流配送中心运输车辆及其周边敏感点的噪声值,采用导则推荐的模型,预测了运输车辆对敏感点的等效声级(Leq)和最大A声级(Lmax),从实测和预测2个途径,明确该物流配送中心运输车辆噪声对周围敏感点的影响,分析各敏感点噪声的超标情况。将等效声级预测结果与实测结果相比较,预测结果稍大于实测结果,两者相差1~2dB(A),表明预测结果可信。根据敏感点噪声超标情况,提出了运输车辆噪声控制对策,以减少该物流配送中心车辆噪声对居民的影响。     

考虑营销成本的库存与运输联合优化三阶段决策模型研究

一般来说,个体最优和整体最优是不一致的,二者之间存在着偏差,这一偏差就是分散优化带来的效率损失。库存与运输联合优化（ITIO）将物流系统中的库存控制和运输管理融合到一个大问题中,去寻求这一联合问题而非单个问题的最优解决方案,可以最优化整个配送系统的运营成本。本文在考虑营销成本条件下,建立ITIO三阶段决策模型,并求解分析模型性质。研究表明：ITIO零售价和营销成本与需求的营销成本弹性、零售商订购成本、供应商生产启动成本、供应商生产成本、运输固定成本和运输可变成本正相关;与需求函数的价格弹性和订货批量负相关;当订购数量相同时,零售商单独优化的营销成本大于ITIO联合优化的营销成本。     

An integrated multi-depot hub-location vehicle routing model for network planning of parcel service

The paper describes why optimal design of depot and hub transportation networks for parcel service providers makes it necessary to develop a generalized hub location and vehicle routing model (VRM). Analogous problems occur for postal, parcel and piece goods service providers. A generalized hub location and VRM is developed which encompasses the determination of the number, locations of hubs and depots and their assigned service areas as well as the routes between the demand points and consolidation points (depots, hubs). Because this task leads to a very complex transport design problem, a heuristic solution concept has to be developed. The applicability to a case study is demonstrated; the case of completely new system configuration for Austria is considered. Management must simultaneously decide the number, location, service areas and routes from demand points to depots and vice versa (the pickup and delivery structure) as well as the number and locations of hubs and the routes of depot–hub and hub–hub transports (the hub location or line haul structure), The developed management support decision model leads for real cases to a tremendous number of some million binary variables as well as continuous variables and million of constraints.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Accelerating the Process of Engineering Change Orders: Capacity and Congestion Effects

Engineering change orders (ECOs) are important drivers of development costs and lead time. This article analyzes the process of administering engineering change orders in the case of the climate control system development within a large vehicle development project. This administrative process encompasses the emergence of a change (e.g., a problem or a market-driven feature change), its management approval, and final implementation. Despite strong time pressure, this process can take several weeks, several months, and, in extreme cases, even over 1 year. Such a long lead time is especially remarkable as the actual processing time for the change typically does not exceed 2 weeks. Based on our case study, we develop an analytical framework that explains how such an extreme ratio between theoretical processing time and actual lead time is possible. The framework identifies congestion, stemming from scarce capacity coupled with processing variability, as a major lead time contributor. We outline five improvement strategies that an organization can use in order to reduce ECO lead time, namely, flexible capacity, balanced workloads, merged tasks, pooling, and reduced setups and batching. © 1999 Elsevier Science Inc.     

The selective pickup and delivery problem: Formulation and a memetic algorithm

The pickup and delivery problem addresses the real-world issues in logistic industry and establishes an important category of vehicle routing problems. The problem is to find the shortest route to collect and distribute commodities under the assumption that the total supply and the total demand are in equilibrium. This study presents a novel problem formulation, called the selective pickup and delivery problem (SPDP), by relaxing the constraint that all pickup nodes must be visited. Specifically, the SPDP aims to find the shortest route that can supply delivery nodes with required commodities from some pickup nodes. This problem can substantially reduce the transportation cost and fits real-world logistic scenarios. Furthermore, this study proves that the SPDP is NP-hard and proposes a memetic algorithm (MA) based on genetic algorithm and local search to resolve the problem. A novel representation of candidate solutions is designed for the selection of pickup nodes. The related operators are also devised for the MA; in particular, it adapts the 2-opt operator to the sub-routes of the SPDP for enhancement of visiting order. The experimental results on several SPDP instances validate that the proposed MA can significantly outperform genetic algorithm and tabu search in terms of solution quality and convergence speed. In addition, the reduced route lengths on the test instances and the real-world application to rental bikes distribution demonstrate the benefit of the SPDP in logistics.     

标准管理系统在普光采气厂的开发与应用

介绍了普光采气厂标准管理信息系统的建立、原理和内容,同时对应用效果进行了分析。该信息系统实现了标准的在线查询,解决了标准管理和生产中的实际问题,获得了较好的经济效益和社会效益。     

PVC手套生产线手模温度在线测量的研究与应用

为了解决PVC手套生产过程中手模温度在线测量难题,开发出一套移动物体在线测温装置。该装置安装红外测温传感器,采用PLC控制的同步跟踪技术对生产线手模进行跟踪,保证红外测温传感器和手模同步并正确测量其温度。用组态软件kingview开发出手模温度在线测量的监控界面,对手模温度进行实时监控。实验结果显示该装置运行稳定,采集的温度可靠。     

电机生产计划计算机优化系统

本文介绍了电机生产计划计算机优化系统.该系统主要由模型优化和数据处理两大部分组成,采用结构化方法进行系统分析与设计.该系统解决了合理、充分地利用有限原材料的问题,为工厂制订更合理、更科学的生产计划提供了必要的信息。     

Lean planning in the semi-process industry, a case study

The lean approach is an idealizing improvement approach that has an enormous impact in the field of operations management. It started in the automotive industry and has since been widely applied in discrete manufacturing. However, extensions to the (semi-) process industry have been much slower. Resource characteristics of the (semi-) process industry obstruct a straightforward application. The notion of the point of discretization for the (semi-) process industry is helpful here. This notion builds on the fact that in most (semi-) process industries there is a point in production where process production turns into discrete production. Downstream of this point lean principles are applicable in a straightforward manner, while upstream lean needs to be interpreted in a more liberal way. In this article we address this issue by a case study. The study considers how the principles of ‘flow’ and ‘pull’ production - suggesting a regular, demand-driven product flow - may be implemented for the (semi-) process industry by introducing cyclic schedules. The conjectures guiding the case study are: (i) Cyclic schedules fit in a lean improvement approach for the semi-process industry, (ii) Cyclic schedules help to improve production quality and supply-chain coordination and (iii) Discrete event simulation is a useful tool in facilitating a participative design of a cyclic schedule. The case study is extensively described to be able to judge how the context of the changes and the intervention process contribute to the results of the intervention.     

An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem

The inventory routing problem (IRP) addressed in this study is a many-to-one distribution network consisting of an assembly plant and many distinct suppliers where each supplies a distinct product. We consider a finite horizon, multi-periods, multi-suppliers and multi-products where a fleet of capacitated homogeneous vehicles, housed at a depot, transport products from the suppliers to meet the demand specified by the assembly plant in each period. The demand for each product is deterministic and time varying. A mathematical formulation of the problem is given and CPLEX 9.1 is run for a finite amount of time to obtain lower and upper bounds. A hybrid genetic algorithm, which is based on the allocation first route second strategy and which considers both the inventory and the transportation costs, is proposed. In addition to a new set of crossover and mutation operators, we also introduce two new chromosome representations. Several medium and small sized problems are also constructed and added to the existing data sets to show the effectiveness of the proposed approach.     

Schedule evaluation in unstable manufacturing environments

This paper provides a new approach to validate the feasibility of schedules of multiple-step mixed-model unstable manufacturing environments with different changeover times. Traditionally, continuous lines in a manufacturing process run the same sequence in order to minimize WIP inventory and lead time. Nevertheless, multiple reasons such as different product mixes or setup times can lead managers to run different sequences in continuous lines. Unfortunately, lack of reliability of supply and demand in these environments makes it difficult to manage product inventories and often leads to starvation due to the discoordination between the schedules of both lines. This approach is based on a new type of visual representation of schedules and an estimate the probability of starvation. It assumes stochastic supply and demand and a predefined schedule sequence based on batches of different sizes.     

CONCURRENT ENGINEERING: CONTEMPORARY ISSUES AND MODERN DESIGN TOOLS EDITED BY HAMID R. PARSAEJ AND WILLIAM G. SULLIVAN Chapman & Hall,London, 1993, xiii + 497 pp. ISBN 0-412-46510-8. List: $75.00.

In a recent paper, Jones and Zydiak [2] discuss the steady state fleet design problem, which has no natural initial distribution of vehicles. For this problem, they develop a new optimality criterion of minimizing annual equivalent cost per vehicle because the traditional optimally criterion of minimizing annual equivalent cost can lead to paradoxical results, as shown by example, when applied to the fleet design problem. In a subsequent note, Hartman [1] argues that this paradox is actually a result of a replacement convention that ignores opportunity costs. In this response, we demonstrate that paradoxical replacement behavior can occur with the traditional criterion even when opportunity costs are accounted for in the replacement analysis. We further conclude that the problems considered respectively by Jones and Zydiak [2] and Hartman [1] are fundamentally different in nature.     

汽车三滤超声波清洗机及其控制系统

为解决汽车三滤清洗困难及减少浪费和污染 ,本文提出用超声波技术清洗汽车三滤 ,介绍了超声波三滤清洗机的工作原理和工艺流程 ,并对其进行了总体设计和自动控制系统设计     

Algorithm portfolios for logistics optimization considering stochastic demands and mobility allowance

The vehicle routing problem with stochastic demand (VRPSD) is a well known NP-hard problem. The uncharacteristic behaviour associated with the problem enhances the computational efforts required to obtain a feasible and near-optimal solution. This paper proposes an algorithm portfolio methodology based on evolutionary algorithms, which takes into account the stochastic nature of customer demand to solve this computationally complex problem. These problems are well known to have computationally complex objective functions, which make their solutions hard to find, particularly when problem instances of large dimensions are considered. Of particular importance in such situations is the timeliness of the solution. For example, Apple was forced to delay their shipments of iPads internationally due to unprecedented demand and issues with their delivery systems in Samsung Electronics and Seiko Epson. Such examples illustrate the importance of stochastic customer demands and the timing of delivery. Moreover, most of the evolutionary algorithms, known for providing computationally efficient solutions, are unable to always provide optimal or near optimal solutions to all the VRPSD instances within allocated time interval. This is due to the characteristic variations in the computational time taken by evolutionary algorithms for same or varying size of the VRPSD instances. Therefore, this paper presents portfolios of different evolutionary algorithms to reduce the computational time taken to resolve the VRPSD. Moreover, an innovative concept of the mobility allowance (MA) in landmoves based on the levy’s distribution function has been introduced to cope with real situations existing in vehicle routing problems. The proposed portfolio approach has been evaluated for the varying instances of the VRPSD. Four of the existing metaheuristics including Genetic Algorithm (GA), Simulated Annealing (SA), Artificial Immune System (AIS), TABU Search (TS) along with new neighbourhood search, are incorporated in the portfolios. Experiments have been performed on varying dimensions of the VRPSD instances to validate the different properties of the algorithm portfolio. An illustrative example is presented to show that the set of metaheuristics allocated to certain number of processors (i.e. algorithm portfolio) performed better than their individual metaheuristics.     

气井出砂对涡流工具携液能力的影响

为分析气井出砂对涡流工具携液能力的影响情况,针对气井井底积液以及井筒中存在固体杂质的问题,提出了一种气井中涡流工具携液携砂的三相流模型。通过对气井含砂与不含砂的情况进行模拟,分析了不同条件下涡流工具的携液作用,得到了气井出砂对液相流动规律、体积分数、速度分布的影响情况。结果表明:出砂量为10%的情况下,气井含砂有利于气井携液。气井含砂使运动阻力增加,液相的运动速度减小,轴向速度分布不规律,紊流程度增强,从而使运动更加复杂,气井对液体的携带作用增强;气井含砂使液相的运动速度减小且分布不规律。研究结果对进一步完善涡流工具的排水采气机理、提升气井的携液携砂效果具有参考价值。