Product mix strategy and manufacturing flexibility

The manufacturing industry is facing a turbulent and constantly changing environment, with growing complexity and high levels of customisation. Any investment solution should address these problems for a dynamic market and within limited budget boundaries, so that companies try to remain competitive. The authors propose a real options model to support firms making important investment decisions, specifically decisions associated with the acquisition of new equipment aimed at allowing firms to increase their manufacturing flexibility for the production of both standard and customized products. This paper is partially based on a real operating experience related to visual finishing technology features in an industrial company that conforms to the definitions of the product mix. The authors’ motivation for this work is driven by firms’ desire to satisfy specific customer needs, and to respond to them quickly under uncertain demand. Our goal, using theories from finance, production management, and product offering management, is to conclude that there is a relevant difference between the evaluation of the technology that is to be chosen, and the potential value due to product mix adaptations that are able to provide the maximum return from investment. We address problems related to standard and customized production systems, and the decision to invest in a set of resources that will enable this choice.     

Topology optimization for minimum mass design considering local failure constraints and contact boundary conditions

This paper studies the optimum design of a 1×2 mechanical optical switch. First, a novel switch configuration is designed with an included antithermal mechanism. Then, parametric programs are developed to automatically generate the solid model and to analyze thermal behavior of the switch. From the analysis of the initial design, it revealed that the amount of transverse offset between fiber tips failed in satisfying the Bellcore specifications. Finally, an integrated program combining CAD software, genetic algorithms, and finite element software was developed for optimum design of optical switches. With the capability of continuously changing critical design parameters of the switch in the integrated design program, the final optimum design satisfying the design constraints and specifications can be found.     

Optimal layout theory: Analytical solutions for elastic structures with several deflection constraints and load conditions

The aim of this note is to outline briefly, in the context of trusses, an optimal layout theory for elastic structures involving deflection constraints for several load conditions. The proposed theory is verified by a simple example, for which the solution by other methods is already known.     

Hamilton-Jacobi inequalities and the optimality conditions in the problems of control with common end constraints

The canonical theory of the necessary and sufficient conditions for global optimality based on the sets of nonsmooth solutions of the differential Hamilton-Jacobi inequalities of two classes of weakly and strongly monotone Lyapunov type functions was developed. These functions enable one to estimate from above and below the objective functional of the optimal control problem and determine the internal and external approximations of the reachability set of the controlled dynamic system.     

Formulations of the capacity planning problem considering manufacturing flexibility

This paper addresses the problem of determining the capacity requirements for a manufacturing system that consists of versatile metal removing machines, each of which may be configured to perform several different operations at varying levels of efficiency and cost. The number of each machine type required and the assignment of each machine type to different processes are determined by minimizing the sum of machine amortization costs and operating costs. Alternative formulations are presented to address non-splitting of a batch and non-splitting of the processing of a part. The formulations are illustrated using numerical examples.     

On boundary conditions for adjoint variables in problems with state variable inequality constraints

This correspondence discusses boundary conditions for adjoint variables in problems with state variable inequality constraints. Particular attention is given to inequality terminal constraints. It is shown that it is important to identify whether the boundary of the state space is "absorbing" or not. An example is given to show the importance of these considerations in determining optimal trajectories.     

Consistency checking and querying in probabilistic databases under integrity constraints

We address the issue of incorporating a particular yet expressive form of integrity constraints (namely, denial constraints) into probabilistic databases. To this aim, we move away from the common way of giving semantics to probabilistic databases, which relies on considering a unique interpretation of the data, and address two fundamental problems: consistency checking and query evaluation. The former consists in verifying whether there is an interpretation which conforms to both the marginal probabilities of the tuples and the integrity constraints. The latter is the problem of answering queries under a “cautious” paradigm, taking into account all interpretations of the data in accordance with the constraints. In this setting, we investigate the complexity of the above-mentioned problems, and identify several tractable cases of practical relevance.     

Unary probabilistic and quantum automata on promise problems

We continue the systematic investigation of probabilistic and quantum finite automata (PFAs and QFAs) on promise problems by focusing on unary languages. We show that bounded-error unary QFAs are more powerful than bounded-error unary PFAs, and, contrary to the binary language case, the computational power of Las-Vegas QFAs and bounded-error PFAs is equivalent to the computational power of deterministic finite automata (DFAs). Then, we present a new family of unary promise problems defined with two parameters such that when fixing one parameter QFAs can be exponentially more succinct than PFAs and when fixing the other parameter PFAs can be exponentially more succinct than DFAs.     

Computation of a multi-objective production planning model with probabilistic constraints

In this paper, a multi-objective production planning model has been presented for a captive plant. The model includes multi-products, multi-plants, and multi-objective with some probabilistic constraints. The probabilistic constraints have been transformed into deterministic constraints assuming the parameters as independent normal random variables. The deterministic problem has been computed with two different methods, namely weighting method and fuzzy programming method. Finally, the integral solution obtained by these two methods have been compared.     

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and electronic commerce to social networking. Many of these applications involve models of diverse data sources. Effective utilisation and evolution of data models, therefore, calls for matching techniques that generate correspondences between their elements. Various such matching tools have been developed in the past. Yet, their results are often incomplete or erroneous, and thus need to be reconciled, i.e., validated by an expert. This paper analyses the reconciliation process in the presence of large collections of data models, where the network induced by generated correspondences shall meet consistency expectations in terms of integrity constraints. We specifically focus on how to handle data models that show some internal structure and potentially differ in terms of their assumed level of abstraction. We argue that such a setting calls for a probabilistic model of integrity constraints, for which satisfaction is preferred, but not required. In this work, we present a model for probabilistic constraints that enables reasoning on the correctness of individual correspondences within a network of data models, in order to guide an expert in the validation process. To support pay-as-you-go reconciliation, we also show how to construct a set of high-quality correspondences, even if an expert validates only a subset of all generated correspondences. We demonstrate the efficiency of our techniques for real-world datasets comprising database schemas and ontologies from various application domains.     

考虑时间与能耗约束的柔性作业车间调度优化

随着能源价格日益上涨以及国家节能减排措施的不断推进,制造业正朝着绿色生产方向转型。针对受调整时间和能耗约束的柔性作业车间调度问题,建立以最大完工时间、总调整时间和总能耗为目标的数学模型。设计改进的NSGA-Ⅱ与禁忌搜索结合的多目标混合算法（MOGATS）进行求解。算法设计三种初始化规则保证初始解的质量和多样性。为提高算法搜索效果,将Pareto等级引入交叉算子中,并在变异算子中加入模拟退火算法提升算法的局部搜索能力。最后,在Pareto前沿中找到各个目标的最优个体作为初始解,进行禁忌搜索以提高解的质量。通过与其他算法的实验结果进行对比,验证MOGATS算法能够有效求解考虑机器调整的柔性作业车间多目标问题。     

On the computational complexity of combinatorial flexibility problems

The concept of flexibility – originated in the context of heat exchanger networks design – is associated with a substructure which allows the same optimal value on the substructure (for example an optimal flow) as in the whole structure, for all the costs in a given range of costs. In this work, we extend the concept of flexibility to general combinatorial optimization problems, and prove several computational complexity results in this new framework. Under some monotonicity conditions, we prove that a combinatorial optimization problem can be polynomially reduced to its associated flexibility problem. However, the minimum cut, maximum weighted matching and shortest path problems have NP-complete associated flexibility problems. In order to obtain polynomial flexibility problems, we have to restrict ourselves to combinatorial optimization problems on matroids.     

Shape and discrete sizing optimization of timber trusses by considering of joint flexibility

The paper presents the shape and discrete sizing optimization of timber trusses with the consideration of joint flexibility. The optimization was performed by the Mixed-Integer Non-linear Programming (MINLP) approach. In the optimization model an economic objective function for minimizing the structure’s self-manufacturing costs was defined. The design conditions in accordance with Eurocode 5 were considered as optimization constraints. The internal forces and deflections were calculated by finite element analysis. The structural stiffness matrix was composed by considering fictiously decreased cross-sectional areas of all the flexibly connected elements. The cross-section dimensions and the number of fasteners were defined as discrete sizing variables, while the joint coordinates were considered as shape variables. The applicability of the proposed approach is demonstrated through some numerical examples, presented at the end of the paper.     

Improving process flexibility through products assignment with bill of material constraints

This paper investigates the effect of operational decisions on improving process flexibility of a flexible manufacturing system, which consists of multiple machine lines. The manufacturing system produces different types of products, whose structures are described by their bills of material (BOMs). When BOM constraints of products are considered, we observe that process flexibility of the flexible manufacturing system depends not only on the structure of each machine line, but also on the assignment decisions of products to machine lines. On the basis of the analysis of a measure for process flexibility with BOM constraints, we develop products assignment models to improve process flexibility of a flexible manufacturing system, which minimize the total demand shortfall of products in the system through assigning products to machine lines. Computational experiments verify the effectiveness of the proposed models on improving process flexibility of a manufacturing system, and sensitivity analyses show performance robustness of our methods.     

Chaos control of performance measure approach for evaluation of probabilistic constraints

Performance measure approach (PMA) is a recently proposed method for evaluation of probabilistic constraints in reliability-based design optimization of structure. The advanced mean-value (AMV) method is well suitable for PMA due to its simplicity and efficiency. However, when the AMV iterative scheme is applied to search for the minimum performance target point for some nonlinear performance functions, the iterative sequences could fall into the periodic oscillation and even chaos. In the present paper, the phenomena of numerical instabilities of AMV iterative solutions are illustrated firstly. And the chaotic dynamics analysis on the iterative procedure of AMV method is performed. Then, the stability transformation method of chaos feedback control is suggested for the convergence control of AMV procedure in the parameter interval in which the iterative scheme fails. Numerical results of several nonlinear performance functions demonstrate that the control of periodic oscillation, bifurcation and chaos for AMV iterative procedure is achieved, and the stable convergence solutions are obtained.