Locating service centers optimizing customers’ perspective criteria

A network of several demand nodes is considered. We want to locate a number of multiserver facilities at some nodes assuming at least one server must be located at each node. Accordingly, the number of servers has to be more than the nodes number. We propose a model for locating these facilities from customers’ perspective in such a way as to minimize the total average queue length, when customers choose the facilities they patronize, by the travel distance (or time) to the facility and the number of servers at the facility. This means that each customer can obtain the service or goods from several (i.e., rather than only one) facilities, according to a probabilistic distribution. Genetic and simulated annealing (SA) algorithms based heuristics are proposed to solve this problem, which belongs to nonlinear integer programming problems. We evaluate the proposed algorithms for the solution quality solving a number of numerical problems. The results indicate that SA whose objective function is around 26% less than that of genetic is of higher performance.     

论企业客户关系管理

客户关系管理系统CRM是把有关市场和客户的信息进行统一管理、共享,并能进行有效分析、处理的新型应用系统,它为企业内部的销售、营销、客户服务等提供全面的支持。帮助企业缩减销售成本、增加收入、寻找扩展业务所需的新市场和新渠道,在提高客户的价值方面CRM具有很广阔的应用空间。     

A fuzzy possibilistic bi-objective hub covering problem considering production facilities, time horizons and transporter vehicles

This paper presents a novel fuzzy possibilistic bi-objective model for a hub covering location–allocation problem with specific features. Considering two major objectives is the main novelty of this problem, comparing to the previous studies. The first objective is to minimize the total costs consisting of (1) covering costs, (2) transportation costs, (3) opening costs of facilities in hubs, (4) reopening costs of facilities in hubs, (5) activating costs of facilities in hubs, and (6) transporters purchasing costs. The second objective is to minimize the sum of the times of shipping commodities by transporters from the origin node to the destination node via hubs. Furthermore, to come closer to reality, the main parameters of the proposed mathematical model are regarded as fuzzy ones. To solve the proposed multi-objective model, four recent approaches are used and the results are compared with each other.     

Variable neighborhood search based evolutionary algorithm and several approximations for balanced location–allocation design problem

This paper introduces balanced location–allocation design problem to tackle a real-world health-care application. The problem involves strategic decisions on locating a predefined number of facilities and allocating a set of customers to the facilities such that minimizes total travel, operating and congestion costs in an uncertain environment. To face more appropriately with the uncertainties, a comprehensive model which takes into account all sources of uncertainty is proposed. Moreover, in order to have a balanced use of installed capacities and/or reduce delays in servicing, congestion-related costs are defined as a power-law function of the trespassed facility’s operating capacity. The developed model is extremely hard to solve because of its inherently high combinatorial nature combined with the uncertainties and the nonlinearities associated to the congestion. Therefore, a new search mechanism based on variable neighborhood search is put forward. This algorithm employs both random and mathematical programming techniques to generate a set of initial solutions. On the other hand, to examine the quality of each move, a linear model which is scenario decomposable is extracted. The validation of the model is studied on an existing application, and the algorithm’s performance is tested on a wide range of instances taken from literature.     

A new hybrid approach to discrete multiple facility location problem

Locating certain facilities in predetermined sites is named the multiple facility location problems (MFLP). The objective of these kinds of problems is locating facilities to serve a given set of customers so that candidate sites and requirements are known. When the new facility sites have to be selected from a given set of candidate sites, the mentioned location problem becomes a discrete multiple facility location problem (DMFLP). In this paper, a special approach of DMFLP is considered where different multiple facilities have to be placed (location decision) and also customers have to be assigned to these facilities (allocation or assignment). The mathematical model of the proposed problem is developed, and with respect to the complexity of solving the mathematical model, especially in large scale, a new hybrid approach is proposed based on tabu search algorithm to solve the problem at each scale. Computational results on several randomly generated problems in comparison with a new proposed lower bound obtained from Lagrangian relaxation indicate that the proposed hybrid approach is both accurate and efficient.     

Modeling and solving the bi-objective capacitated location-routing problem with probabilistic travel times

The location-routing problem (LRP) is a relatively new research area within location analysis that concerns simultaneously both the problems of location of facilities and routing of vehicles among the established facilities and the demand points. In this work, we address the capacitated LRP with probabilistic travel times, which may arise in many practical contexts in logistics and supply chain management, and present some bi-objective mathematical programming formulations to model the problem using different stochastic programming approaches. The first objective is to minimize the overall system-wide costs, while the second objective concerns minimization of the maximum delivery time to the customers. In all the cases, the deterministic equivalents of the stochastic models have been extracted. To solve the resulted models, a variable neighborhood descent-based heuristic is proposed and finally computational study is performed and numerical results are reported.     

An ant colony system approach for fuzzy traveling salesman problem with time windows

Traveling salesman problem with time windows (TSPTW) is a well-known problem in logistics management. It seeks to find a minimum cost tour among customers while all customers are visited at their time windows. To better reflect the real situations of logistics management, this paper concentrates on customers’ satisfaction aspect of TSPTW, extends the basic mathematical modeling of the problem to fuzzy traveling salesman problem with time windows (FTSPTW), and presents an ant colony system algorithm to solve the problem. One advantage of this new modeling is its flexibility which enables us to optimize the delivery process in the network of customers with different satisfaction patterns and different priorities. The other advantage is that by the use of fuzzy time windows, not only customers’ preference for tolerable interval of time for service but also desirable time for service can be considered. Numerical results for a well-known benchmark problem and a real case study both confirm that optimization of the customers’ satisfaction is completely different from traditionally minimizing the total traveling time as well as the proposed algorithm which considers that customers’ favorites is completely superior to the algorithm that only pays attention to minimizing total travel time. These results provide an opportunity for future comparisons of different solution methods for the FTSPTW.     

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.     

DYNAMIC RELOCATION OF PLANT／WAREHOUSE FACILITIES：A FAST COMPACT GENETIC ALGORITHM APPROACH

The problem of dynamic relocation and phase-out of combined manufacturing plant and warehousing facilities in the supply chain are concerned. A multiple time/multiple objective model is proposed to maximize total profit during the time horizon, minimize total access time from the planfwarehouse facilities to its suppliers and customers and maximize aggregated local incentives during the time horizon. The relocation problem keeps the feature of NP-hard and with the traditional method the optimal result cannot be got easily. So a compact genetic algorithm (CGA) is introduced to solve the problem. In order to accelerate the convergence speed of the CGA, the least square approach is introduced and a fast compact genetic algorithm (fCGA) is proposed. Finally, simulation results with the fCGA are compared with the CGA and classical integer programming (IP). The results show that the fCGA proposed is of high efficiency for Pareto optimality problem.     

Intranet/Extranet/Internet-Based Quality Information Management System in Expanded Enterprises

Because of e-commerce and the global economy, industries are challenged by world markets and modern enterprise morphologies, such as agile supply chains, expanded companies and virtual enterprises. Enterprises are thinking more and more about the market, customers and suppliers. Product quality is judged by the global market and the customers in the world village, and not only by the domestic market and customers. Enterprise quality assurance systems not only cover internal functional departments in an enterprise, but are expanding to external parties, such as customers, partners and suppliers, so, an expanded enterprise’s core competencies or leadership capabilities in quality assurance have to be strengthened by the complementary capabilities of partners. The traditional quality assurance technologies have to be innovated. It is reasonable that "customer focus" and "mutually beneficialsupplier relationships" blend into the core concepts of a quality management philosophy. As tools used by enterprises to support quality management, quality information management systems (QIMS) have to capture quality information from both internal and external parties, and to facilitate the communication environment, in order to share quality information among enterprises, customers and suppliers. Because of this, it is impossible for a traditional quality information management system based on the Intranet to meet these needs. In this paper, a model of the expanded enterprise is extended. A concept model and a functional model of the quality information management system based on Internet/Extranet/Intranet (IEI-QIS) are proposed. The system is able to integrate quality information from the enterprise, product customers and suppliers, and serves as a powerful tool to benefit the quality management of modern enterprises. A browser/server-based and the three-layer system architecture of IEI-QIS are also investigated. ID="A1"Correspondance and offprint requests to: Tang Xiaoqing, School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100083, PR China. E-mail: tanghuan@public.fhnet.cn.net     

Effect of reconfiguration costs on planning for capacity scalability in reconfigurable manufacturing systems

In a globally competitive market for products, manufacturers are faced with an increasing need to improve their flexibility, reliability, and responsiveness to meet the demands of their customers. Reconfigurable manufacturing systems (RMS) have become an important manufacturing paradigm, because they broadly encompass the ability to react efficiently to this environment by providing the exact capacity and functionality needed when needed. This paper studies how such new systems can manage their capacity scalability planning in a cost effective manner. An approach for modeling capacity scalability planning is proposed. The development of the model is based on set theory and the regeneration point theorem which is mapped to the reconfigurable manufacturing paradigm as the capacity scalability points of that system. The cost function of the model incorporates both the physical capacity cost based on capacity size and costs associated with the reconfiguration process which referred to as the scalability penalty cost and scalability effort cost. A dynamic programming (DP) approach is manipulated for the development of optimal capacity scalability plans. The effect of the reconfiguration costs on the capacity scalability planning horizon and overall cost is investigated. The results showed the relation between deciding on the optimal capacity scalability planning horizon and the different reconfiguration costs. Results also highlighted the fact that decreasing costs of reconfiguration will lead to cost effective implementation of reconfigurable manufacturing systems.     

面向大规模定制的生产计划研究

激烈的市场竞争要求企业能快速响应客户的个性化产品需求,为单个客户或小批量多品种的市场定制生产产品。大规模定制能以大规模生产的成本和速度,为客户提供个性化设计的产品和服务。从大规模定制生产模式的特点出发,分析模块化制造物料清单(MBOM,Manufacturing Bill of Material)的基本构成。在MBOM模块化的基础上,基于延迟区分(Postponement Differentiation)策略建立大规模定制模式下的双重MPS计划管理模式,针对零部件的通用需求和定制需求分别制定计划,充分保证客户订单交货期,同时也提高了生产过程的柔性。     

鲜奶采购计划的改进自适应罚函数遗传算法

奶制品加工厂主要从总部采购鲜奶(生产),也会从当地奶农采购部分鲜奶(外包)。出于能力和策略的考虑,两种来源的鲜奶采购量均有限;考虑到客户允许奶制品延期交货,相应的鲜奶也可延期交货,生产、外包和库存/延期交货成本均为一般凹函数,问题是以最小的总成本来满足规划期的鲜奶需求。为求解该问题,设计了一种新的基于群体可行状态和个体约束违背程度的自适应惩罚方案,据此设计了求解该问题的遗传算法。为测试算法的性能,先进行了算子组合和遗传算子概率的选择实验,选出最适合的算子和算子概率;在此基础上,针对4个问题实例,通过50次运行,测试了所提自适应罚函数相对4种常见罚函数的优势。     

A multi-echelon reverse logistics network design for product recovery—a case of truck tire remanufacturing

Due to increasing environmental deterioration, government regulations, social responsibilities, resource reduction, and economic factors, many companies are engaged in the product recovery business. Product recovery refers to the set of activities designed to reclaim value from a product at the end of its useful life. Due to the increasing number of vehicles in the country like India, large quantities of used tires are generated every year, and proper disposal of these used tires creates a significant problem in the day-to-day life. An alternative way to recover the value (tire remanufacturing also called retreading) from the used tire is proposed in this work. The implementation of such remanufacturing system usually requires an appropriate reverse logistics network for choosing the physical locations, facilities, and transportation links to convey the used products from customers to the remanufacturing facility and from there to secondary markets. The main objective of this work is to develop a mixed integer nonlinear programming model for maximizing the profit of a multi-echelon reverse logistics network and also to present a real-life case study of truck tire remanufacturing for the secondary market segment. The proposed model is solved using LINGO 8.0 optimization solver which provides the decisions related to the number of facilities to open, their locations, and also the allocation of the corresponding product flows. Finally, it is concluded that the choice of using retreaded tires is a profitable one by the way of cost reduction. Sensitivity analysis of the model is also presented to find the maximum allowable distance between the customers and initial collection points.     

Greedy randomised dispatching heuristics for the single machine scheduling problem with quadratic earliness and tardiness penalties

In this paper, we present greedy randomised dispatching heuristics for the single-machine scheduling problem with quadratic earliness and tardiness costs and no machine idle time. The several heuristic versions differ, on the one hand, on the strategies involved in the construction of the greedy randomised schedules. On the other hand, these versions also differ on whether they employ only a final improvement step or perform a local search after each greedy randomised construction. The proposed heuristics were compared with existing procedures as well as with optimum solutions for some instance sizes. The computational results show that the proposed procedures clearly outperform their underlying dispatching heuristic, and the best of these procedures provide results that are quite close to the optimum. The best of the proposed algorithms is the new recommended heuristic for large instances as well as a suitable alternative to the best existing procedure for the larger of the middle-sized instances.     

浅谈“冲洗”对密封的影响

机械密封产品在石油化工、炼油、食品等行业已经得到普遍推广和使用,机械密封在保证设备的安全运转的同时,为企业节约了大量的维护、维修成本,提高了企业的效益。在新的市场环境下,市场对机械密封性能及其使用寿命提出了新的要求,机械密封的性能及其使用寿命,与其选型、结构、选材、工况环境等因素都密不可分,除此之外,正确选择和设计“冲洗”能起到提高机械密封性能和延长机械密封使用寿命的作用。     

压缩遗传算法在供应链布局中的应用

针对供应链广泛存在的工厂／仓库的布局问题，以工厂固定期限内的最大化利润、企业到客户和供应商之间的最小访问时间，以及以当地优惠政策的最大量化值为目标函数，提出一种多时段、多目标的模型。由于该类问题既是Pareto优化问题，又是典型的NP难题，用通常的寻优方法不会得到满意的结果，因此，采用压缩遗传算法来解决。同时，为了加快压缩遗传算法的收敛速度，引入最小二乘方法对概率矩阵的元素值进行估计，提出了快速压缩遗传算法。最后，根据生产实践中得到的数据进行了仿真，通过压缩遗传算法和整数规划方法的比较，验证了快速压缩遗传算法在解决多目标优化问题上的有效性。     

Two meta-heuristics for a multi-period minisum location–relocation problem with line restriction

This paper investigates a multiperiod rectilinear distance minisum location problem, as a mixed-integer nonlinear programming (MINLP) model with a line-shaped barrier restriction, in which the starting point of the barrier uniformly distributed in the plane. The objective function of this model is to minimize the sum of the costs associated with the expected weighted barrier distance of the new facility from the existing facilities and the costs incurred by location-dependent relocation during the planning horizon. Then, a lower bound based on the forbidden region is presented. To show the validation of the presented model, a number of numerical examples are illustrated. The associated results show that the optimization software is effective for small-sized problems. However, the optimization software is unable to find an optimum solution for large-sized problems in a reasonable time. Thus, two meta-heuristics, namely genetic algorithm (GA) and imperialist competitive algorithm (ICA), are proposed. Finally, the associated results are compared and discussed.     

基于遗传算法的柔性制造系统机床选择问题研究

由于激烈的市场竞争环境,灵活的制造商应该以最快的速度向市场推出产品,以最少的成本进行生产,从而拥有使消费者满意的巨大能力.而具有快速时间响应和高度柔性的制造系统是必要的.在假设的条件下,构建基于零件加工时间和成本加权和为目标的柔性制造系统机床选择数学模型,在模型中考虑机床的维修成本.用C语言实现遗传算法在柔性制造系统机床选择中的应用,并与以前的例子进行比较.最后通过实验对遗传算法的参数进行分析.     

Ahp model for the selection of partner companies in virtual enterprises

Rising product variety and complexity, shorter time frames to respond, and the continual need to gain new capabilities through innovativeness force the trend of outsourcing to be replaced by strategic alliances, where enterprises or individuals work together towards a common goal and share their responsibilities as well as their profits. Recent developments in information technology have enabled relatively inexpensive, reliable and fast networking to support such alliances in real time. In this context, the virtual enterprise (VE) represents an appropriate cooperation alternative and competitive advantage for the enterprises. VE is a temporary network of independent companies -- suppliers, customers, even rivals -- linked by information technology (IT) to share skills, costs and access to one another’s markets. In this emerging business model of virtual enterprise, the decision support functionality, which addresses issues such as partner company selection, is an important domain to be studied. In this paper, we propose an analytic hierarchy process model to contribute in the selection of the partner companies in the virtual enterprises. A case example is also covered to validate the feasibility of the adoption of the model in virtual enterprise situations.