Aggregation and disaggregation in hierarchical production planning

This paper reports on a simulation study of hierarchical planning procedures, which can support a material requirements planning system. Data for this study have been obtained from a Swedish manufacturing company. The three final products considered in the simulations represent a major part of this company.An aggregate plan in terms of product groups and machine groups is derived with the aid of an aggregate model. This plan is then disaggregated by changing order release times obtained from material requirements planning, and by distributing extra capacity among individual machines.The results indicate that our methods in general perform significantly better than a comparable reference case without the supporting hierarchical planning process. In our simulation experiments we evaluate different design features, like disaggregation procedures and methods for aggregating items and machines.     

MARKEX: An intelligent decision support system for product development decisions

A new methodology for the development of new products and an intelligent DSS, named MARKEX, which is an implementation of this methodology, are presented in this paper. The system acts as a consultant for marketers, providing visual support to enhance understanding and to overcome lack of expertise. The databases of the system are the results of consumer surveys, as well as financial information of the enterprises involved in the decision making process. The system's model base encompasses statistical analysis, preference analysis, and consumer choice models. MARKEX incorporates partial knowledge bases to support decision makers in different stages of the product development process.     

Forest planning at the tactical level

Forest management and planning can involve large tracts of land involving numerous areal units. One approach to plan activities for a forested region over decades involves breaking down decision making into three components: strategic, tactical, and operational. Each level of the management hierarchy can involve the development and application of optimization models. These models typically aid in exploring management alternatives as well as multi-objective tradeoffs. Even though a strategic model can provide support for long term management at a broad scale, solutions may not be feasible at an operational level. Tactical level modeling helps to bridge solutions reached at a strategic level using operational planning information. This paper presents several tactical level planning models that have been developed as a part of a research effort supported by the US Forest Service. These models have been utilized in land use management and planning by the US Forest Service through a specially developed spatial decision support system.     

Some New Techniques in Transportation Planning<Superscript>†</Superscript>

The development of urban transportation planning models has accelerated in the past decade, until they are now widely accepted aids to the urban decision process. However, the models have had limited impact upon individual decisions, because of their complexity and size. In the absence of radical new approaches to planning, a methodology is suggested to complement the existing procedures.This methodology, which is referred to as "perturbation", is illustrated by reference to the choice of a future network. Some results are presented for the budgeting of capital for a set of investments.     

An advanced quality function deployment model using fuzzy analytic network process

Quality function deployment (QFD) is a customer-oriented design tool used to ensure that the voice of customers is employed throughout the product planning and design stages. QFD uses the house of quality (HOQ), which is a matrix that provides a conceptual map for inter-functional planning and communication. In this paper, an advanced QFD model, based on fuzzy analytic network process (ANP) approach, is proposed to systematically take into account the interrelationship between and within the QFD components. The proposed method is aimed at expanding the current research scope from the product planning phase to the part deployment phase to provide product developers with more valuable information (ex. the importance and bottleneck level of part characteristics). Both customer requirements and the company’s production demands will be used as the inputs for the QFD process to enhance the completeness and accuracy of the QFD analysis results. A case study is presented to illustrate the application of the proposed method.     

A framework for participatory budget elaboration support

Participatory budgets are becoming increasingly popular in many municipalities all around the world. The underlying idea is to allow citizens to participate in the allocation of a municipal budget. Little decision support methodology is used in this type of activities, frequently based on physical meetings and some kind of voting mechanism. We describe models and methods to support the elaboration of a participatory budget. We model this problem as one of resource allocation, in which citizens attempt to maximize group satisfaction in view of multiple criteria, subject to, possibly, other constraints. Based on a negotiation approach, we propose a general methodology to deal with such a problem.     

How to benefit from decision analysis in environmental life cycle assessment (LCA)

Environmental life cycle assessment (LCA) is one method to support environmental information needs by multi-attribute product evaluations. LCA describes the environmental effects associated with a product, process or activity over its whole life cycle by calculating the material and energy requirements as well as emissions to air, water and soil and by assessing the environmental impacts of those. An LCA study has both objective and subjective steps. So far, LCA has been developed without much consideration of the literature on decision modelling. We want to show that approaches and tools from decision analysis would be beneficial both in the planning of an LCA study and in the interpretation and understanding of the results. We describe the LCA methodology and application, and discuss how the integration of decision analysis and LCA could improve LCA as a tool for decision making. We use an LCA study on beverage packaging systems to illustrate the new approach.     

响应建模法在改进产品设计中的应用

本文指出双重响应曲面方法的一些局限性,介绍了响应建模法在参数设计中的应用及其优点,也指出了响应建模法与双重响应曲面方法的联系。本文还通过一个实例说明响应建模法能从试验数据中获取更多的信息。我们认为响应建模法能在改进产品的参数设计起到重要作用,具有一些双重响应曲面方法不能替代的优点。     

Aggregation and the design of models for medium-term planning of production

A major issue in the design of an aggregate multi-period model for medium-term planning of production is the determination of the aggregation level of the variables. In the process of model design, one has to examine if and how the outcomes of the model are effected by applying different modes and levels of aggregation. This is especially important with regard to those outcomes which will be used for medium-term decisions and for laying out short-term and detailed plans. Also dependent on the aggregation level is the operational convenience of the model for decision support. In this paper it will be shown that simulation experiments with a preliminary model for medium-term planning can yield valuable information to aid this design problem.     

A structural optimization approach for passanger car tires with consideration of uncertainties

In order to support the design process of passenger car tires, a multi-objective optimization approach based on Finite Element Analysis (FEA) can be utilized. Providing a reliable and high quality design requires the consideration of data uncertainty within the optimization process. This uncertainty is caused predominantly by instable production conditions of tire components as well as incomplete information concerning e.g. loading. In order to capture the state of information which is indeed available in such engineering applications, an uncertainty model, which enables modelling fragmentary or dubious information as well as mathematical formulation of expert specifications and evaluations has to be applied. The presented requirements are fulfilled by the uncertainty model fuzziness. Therefore, an approach of multi-objective optimization with consideration of fuzzy quantities was developed. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Agricultural product development using multidimensional and multicriteria analyses: The case of wine

Multicriteria analysis and multidimensional statistical methods can collaborate and offer new prospects in the fields of decision support and management in general. This paper presents a survey-based methodology which combines a multicriteria model for the consumer's preference analysis as well as classical data analysis models to design agricultural products. The new products are developed in such a way that they eventually achieve the maximum possible market share. A real study for the Athenian wine market is presented for illustration. The paper concludes with some further reccomendations.     

Diseño óptimo robusto utilizando modelos Kriging: aplicación al diseño óptimo robusto de estructuras articuladas

Conventional methods addressing the robust design optimization problem of structures usually require high computational requirements due to the nesting of uncertainty quantification within the optimization process. In order to address such a problem, this work proposes a methodology, based on Kriging models, to efficiently assess the uncertainty quantification in the optimization process. The Kriging model approximates the structural performance both in the design domain and in the stochastic domain, which allows to decouple the uncertainty quantification process and the optimization process. In addition, an infill criterion based on the variance of the Kriging prediction is included to update the Kriging model towards the global Pareto front. Three numerical examples show the applicability and the accuracy of the proposed methodology. The results show that the proposed method is appropriate to solve the robust design optimization problem with reasonable accuracy and a considerably lower number of function calls than required by conventional methods.     

A web-based methodology for product design evaluation and optimisation

The authors have developed a methodology that takes advantages of the World Wide Web to analyse and develop optimal new product designs. This paper describes the methodology and illustrates its application to a case study involving the design of an actual Web site where music CDs are sold. The proposed methodology has the following features: (a) it is based on a design inspired by conjoint analysis; (b) it involves unobtrusive electronic measurement of the actual behavior of Web users who remain undisturbed by experimental factors; and (c) it utilises an integer programming approach to seek optimal Web site configurations. The methodology uses limited dependent variable methods to develop response models that provide the basis for the development of objective functions for an optimisation model. The optimisation model can consider either single or multiple objective functions by using a Pareto optimum approach.     

The development of modular-based design in considering technology complexity

Applying modularity in the designing of products has been extensively researched recently to reduce the delay of product development. This paper presents a methodology of modular-based design in the conceptual stage of systems to support concurrent engineering (CE). First, the functions (Fs) are classified into different types of modules according to the correlation in design by using fuzzy cluster identification. Second, the optimal module type is selected based on the considerations of the manufacture and assembly complexities of the system for progressive parallel design. Third, the design priority of Fs within a module is scheduled by measuring the information content of Fs. As a result, the traditional design process is arranged as a series-parallel action to reduce the design time of products. Finally, an automated guided vehicle (AGV) system is used as an example to describe this method.     

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler’s demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method.     

Database-Oriented Design of Planning Models

There exists a close correspondence between relational databaseorganization and the structure of mathematical planning models.This correspondence will be used (i) for the explanation ofstandard planning models, (ii) for the integration of planningmodels in information systems, and (iii) for the process ofsystematic design of large-scale planning models.     

Formation of a strategic manufacturing and distribution network with transfer prices

We propose a profit maximization model for the decision support system of a firm that wishes to establish or rationalize a multinational manufacturing and distribution network to produce and deliver finished goods from sources to consumers. The model simultaneously evaluates all traditional location factors in a manufacturing and distribution network design problem and sets intra-firm transfer prices that take account of tax and exchange rate differentials between countries. Utilizing the generalized Benders decomposition approach, we exploit the partition between the product flow and the cash allocation (i.e., the pricing and revenue assignment) decisions in the supply chain to find near optimal model solutions. Our proposed profit maximizing strategic planning model produces intuitive results. We offer computational experiments to illustrate the potential valuable guidance the model can provide to a firm's supply chain design strategic planning process.     

Scheduling and control,performance measures and discrete event simulation

There are a growing number of finite capacity scheduling tools which are in use and available to industry. To be fully effective, a scheduling system needs to be incorporated within a control methodology which enables shop-floor performance to be analysed and, when necessary, corrective actions to be formulated. Manufacturing system performance, however, is not only dependent upon short-term planning decisions, but is also constrained by the capability for which it is designed. Hence, any control methodology should be based on a consistent set of performance measures and well defined procedures which help to integrate decision making at all levels in the order fulfilment process. The paper examines the distinctive roles of process optimisation and process control in the decision hierarchy; it classifies a set of measures of performance and other system variables according to the functions they serve in manufacturing control, and suggests a hierarchical process control methodology. The role of discrete event simulation techniques in linking decisions on manufacturing system design and production planning/control is also discussed.     

An operational profit sharing and transfer pricing model for network-manufacturing companies

New age companies are forging partnerships with other firms to market products that have been assembled through manufacturing activities distributed at different locations. These locations belong to more than one company and the product passes through these different sites during its manufacturing stages. This manufacturing collaboration is known as network-manufacturing. According to the network philosophy, companies form alliances to manufacture a product and share in its operating profits. This paper proposes a framework and methodology for profit sharing and transfer-pricing between network companies. We propose a paradigm that enables maximization of operating profits by the manufacturing-network in its larger supply chain, suggesting a departure from the model that maximizes profits for the individual company within the sphere of its own supply chain.