Using economic X control chart design methodology to estimate and optimize machine efficiency in the case of multimachine assignments

Estimation and optimization of machine efficiency in the case of multi machine assignments is a difficult issue for some industries such as textile industry, due to the machine interference. Although the problem is not new, the solutions proposed are not full satisfactory. For example, the analytical formulas are not suitable for high number of machines; queuing theory approaches are complex and impractical for mill managers. On the other hand, simulation methodology seems to be a perfect tool to estimate and analyze; however, the simulation package programs are expensive and are not suitable for systematic optimization. In this paper, Duncan's economic control chart design methodology is proposed as an alternative way for one of the oldest industrial problems. This study shows that this new approach is a more efficient solution to this stochastic problem. Copyright © 2009 John Wiley & Sons, Ltd.     

A differentiated service scheme to optimize website revenues

We consider a website host server with web quality of service (QoS) capabilities to offer differentiated services. A quantitative modelling framework is set up to analyse the economic benefits of differentiated services and to build optimization models for managing the website host's connection bandwidth to the Internet (which is assumed to be the bottleneck factor determining the QoS). Three models are formulated corresponding to three operational scenarios to provide differentiated services. The first is for the marketing manager to classify visit requests as premium or basic when the information technology (IT) manager has already reserved bandwidths for the two classes, and the second is for the IT manager to allocate the total available bandwidth to each class when the marketing manager has already designated which visit requests are premium and which are basic. The third is for the joint optimization of request classification and bandwidth allocation when centralized coordination is possible. Analytic results are obtained for a special case that corresponds to very impatient customers requesting large amounts of data. Qualitative insights gained and numerical results obtained strongly support the implementation of differentiated services. More interestingly, the decentralized models that use simple and rough-cut rules yield solutions almost as good as the joint optimization model.     

A model to optimize placement operations on dual-head placement machines

Dual-head placement machines are important in the assembly of circuit cards because they offer the capability to place large components accurately. This paper presents a novel column-generation approach for optimizing the placement operations of a dual-head placement machine with the ultimate goal of improving the efficiency of assembly operations. Research objectives are a model that reflects relevant, practical considerations; a solution method that can solve instances within reasonable run times; and tests to establish computational benchmarks. Test results demonstrate the efficacy of our optimization approach on problems of realistic size and scope.     

A methodology to customize pull control systems

The objective of this paper is to develop a methodology for customizing pull control systems, replacing traditional control systems such as Kanban, Conwip, and Base Stock. The basic principle is to start with a pull control system that connects each stage of a given production line with each preceding stage; next, the optimization of the corresponding simulation model shows which of these potential control loops are actually implemented. The result of this methodology may be one of the traditional systems, but it may also be one of the following three new types: (1) the total line may be decomposed into several segments, each with its own classic control system, (2) the total line or its segments may combine different traditional systems, or (3) the line may be controlled through a new type of control system. Indeed, these three systems are found in a simulation experiment with a set of twelve production lines. These twelve lines are selected through a statistical design with ten factors that characterize production lines.     

A Sino-German semi-virtual seminar in mathematics education

In summer 2006 the University of Education in Weingarten, Germany, and East China Normal University, Shanghai, performed a semi-virtual seminar with mathematics students on “Mathematics and Architecture”. The goal was the joint development of teaching materials for German or Chinese school, based on different buildings such as “Nanpu Bridge”, or the “Eiffel Tower”. The purpose of the seminar was to provide a learning environment for students supported by using information and communication technology (ICT) to understand how the hidden mathematics in buildings should be related to school mathematics; to experience the multicultural potential of the international language “Mathematics”; to develop “media competence” while communicating with others and using technologies in mathematics education; and to recognize the differences in teaching mathematics between the two cultures. In this paper we will present our ideas, experiences and results from the seminar.     

Learning to optimize: A tutorial for continuous and mixed-integer optimization

Learning to optimize(L2O) stands at the intersection of traditional optimization and machine learning, utilizing the capabilities of machine learning to enhance conventional optimization techniques. As real-world optimization problems frequently share common structures, L2O provides a tool to exploit these structures for better or faster solutions. This tutorial dives deep into L2O techniques, introducing how to accelerate optimization algorithms, promptly estimate the solutions, or even reshape...     

A hierarchy machine: Learning to optimize from nature and humans

This article proposes a competent hierarchical optimization method called the hierarchical Bayesian optimization algorithm (hBOA). hBOA extends the Bayesian optimization algorithm (BOA) by incorporating three important features for robust and scalable optimization of hierarchical problems: proper decomposition, chunking, and preservation of alternative solutions. Additionally, the article proposes a class of difficult hierarchical problems called hierarchical traps. hBOA is shown to provide a scalable solution to the class of hierarchically decomposable problems and anything easier. Specifically, hBOA can solve hierarchical traps and other nearly decomposable problems in approximately O(n^1.55 log n) to O(n²) function evaluations, where n is the number of decision variables in the problem. © 2003 Wiley Periodicals, Inc.     

A methodology to create robust job rotation schedules

This research proposes a methodology for developing robust job rotation schedules to reduce the likelihood of low back injury due to lifting. We consider settings that have uncertain task demands and different worker profiles in order to simulate real settings. We begin by considering deterministic versions of the problem and solve these using mathematical programming. Because mathematical programming cannot be readily applied to stochastic versions of the problem, heuristic solution methods are developed. The effectiveness of these methods is demonstrated by comparing the results with provably optimal solutions from the deterministic problems and with an enumerative approach that is applied to the stochastic version of the problem. Across the test problems, the proposed heuristics are effective at finding good job rotation solutions. The proposed methods could also be applied to solve other job rotation objectives such as maximizing productivity and reducing exposure to other work environmental factors such as excessive noise.     

An approach to optimize block surgical schedules

We provide an approach to optimize a block surgical schedule (BSS) that adheres to the block scheduling policy, using a new type of newsvendor-based model. We assume that strategic decisions assign a specialty to each Operating Room (OR) day and deal with BSS decisions that assign sub-specialties to time blocks, determining block duration as well as sequence in each OR each day with the objective of minimizing the sum of expected lateness and earliness costs. Our newsvendor approach prescribes the optimal duration of each block and the best permutation, obtained by solving the sequential newsvendor problem, determines the optimal block sequence. We obtain closed-form solutions for the case in which surgery durations follow the normal distribution. Furthermore, we give a closed-form solution for optimal block duration with no-shows.     

A methodology to solve large-scale cooperative transportation planning problems

In this paper, we suggest a methodology to solve a cooperative transportation planning problem and to assess its performance. The problem is motivated by a real-world scenario found in the German food industry. Several manufacturers with same customers but complementary food products share their vehicle fleets to deliver their customers. After an appropriate decomposition of the entire problem into sub problems, we obtain a set of rich vehicle routing problems (VRPs) with time windows for the delivery of the orders, capacity constraints, maximum operating times for the vehicles, and outsourcing options. Each of the resulting sub problems is solved by a greedy heuristic that takes the distance of the locations of customers and the time window constraints into account. The greedy heuristic is improved by an appropriate Ant Colony System (ACS). The suggested heuristics to solve the problem are assessed within a dynamic and stochastic environment in a rolling horizon setting using discrete event simulation. We describe the used simulation infrastructure. The results of extensive simulation experiments based on randomly generated problem instances and scenarios are provided and discussed. We show that the cooperative setting outperforms the non-cooperative one.     

A model to optimize project resource allocation by construction of a balanced histogram

This paper examines a scheduling method to improve productivity in resource-constrained projects. When resources are nonrenewable the duration of each activity has only one value. Optimal solutions are derived through criticalism of groups of activities using the same resource so as to eliminate interruption times and associated costs. The corresponding resource histogram is balanced and its design is derived by means of a program suitable for personal computer implementation.In the case where resources are renewable, activity durations are resource driven. We introduce a new view of discreetness for activity execution times which enables us to obtain optimal solutions relating to the cost functions of the activities.Finally we account for doubly constrained resources by (a) defining a maximum level of resource utilization and a maximum cost increase per period of usage of renewable resources and (b) considering as acceptable only those optimal solutions which keep total cost increase for the overall project below a tolerable limit.An application example is given using personal computer and commercially available software.     

A holistic methodology for modeling consumer response to innovation

A general structural equation model for representing consumer response to innovation is derived and illustrated. The approach both complements and extends an earlier model proposed by Hauser and Urban. Among other benefits, the model is able to take measurement error into account explicitly, to estimate the intercorrelation among exogenous factors if these exist, to yield a unique solution in a statistical sense, and to test complex hypotheses (e.g., systems of relations, simultaneity, feedback) associated with the measurement of consumer responses and their impact on actual choice behavior. In addition, the procedures permit one to model environmental and managerially controllable stimuli as they constrain and influence consumer choice. Limitations of the procedures are discussed and related to existing approaches. Included in the discussion is a development of four generic response models designed to provide a framework for modeling how consumers behave and how managers might better approach the design of products, persuasive appeals, and other controllable factors in the marketing mix.     

A methodology to select suppliers to increase sustainability within supply chains

Central European Journal of Operations Research - Sustainability practice within supply chains remains in an early development phase. Enterprises still need tools that support the integration of...     

New heuristics for over-constrained flight to gate assignments

We consider the over-constrained Airport Gate Assignment Problem where the number of flights exceed the number of gates available, and where the objectives are to minimize the number of ungated flights and the total walking distances. The problem is formulated as a binary quadratic programming problem. We design a greedy algorithm and use a Tabu Search meta-heuristic to solve the problem. The greedy algorithm minimizes ungated flights while we devise a new neighbourhood search technique, the Interval Exchange Move, which allows us flexibility in seeking good solutions, especially when flight schedules are dense in time. Experiments conducted give good results.     

Equilibration of matrices to optimize backward numerical stability

An equilibration is introduced that minimizes the maximum ratio of the upper bounds for the backward rounding error and the inherent error in the given data. This can be applied to the solution of systems of linear equations and to the linear eigenproblem.     

Controller design to optimize a composite performance measure

This paper studies a mixed objective problem of minimizing a composite measure of thel ₁, ₂, andl -norms together with thel -norm of the step response of the closed loop. This performance index can be used to generate Pareto-optimal solutions with respect to the individual measures. The problem is analyzed for discrete-time, single-input single-output (SISO), linear time-invariant systems. It is shown via Lagrange duality theory that the problem can be reduced to a convex optimization problem with a priori known dimension. In addition, continuity of the unique optimal solution with respect to changes in the coefficients of the linear combination that defines the performance measure is estabilished.This research was supported by the National Science Foundation under Grants No. ECS-92-04309, ECS-92-16690 and ECS-93-08481.     

Heuristical labour scheduling to optimize airport passenger flows

We describe the development and implementation of a decision support system for the optimization of passenger flow by trading off service quality and labour costs at an airport. The system integrates a simulation module with an optimization module that requires that Dantzig's labour scheduling problem be solved in the order of thousands of times. We developed a customized scatter search to give the system the capability of finding high-quality solutions to the labour scheduling problems in short computational times. Our experiments verify that our scatter search implementation meets the needed requirements.     

A reduced beam and joint concept modeling approach to optimize global vehicle body dynamics

Ideally, NVH simulations become available already in the concept phase of vehicle development. The initial computer-aided design (CAD) can then be improved (by already including countermeasures), and the feasibility to balance NVH with other performance attributes is increased. In this early design stage, when exact geometrical information is not or scarcely available, conventional virtual prototyping techniques based on detailed CAD and FE models are not directly applicable. A state-of-the-art overview of concept NVH simulation methods in vehicle industry is given.This paper then presents a “Reduced Beam and Joint Modeling” approach to analyze and optimize the global bending and torsion modes of a vehicle body. Concept modifications in the body beam-like sections and in the joints are analyzed using the body reduced modal model. This small-sized model can be used to quickly and accurately optimize the low-frequency vehicle performance. The modifications are considered with respect to the existing (predecessor) model. Equivalent beam properties are estimated from the body FE model; modifications in the beam-like sections are then implemented with beam elements from a standard FE library. The joint modifications are considered through static superelements: stiffness formulations between the end points of the joint connected to the beam layout. The validity of the approach is first demonstrated on simple example models. An industrial vehicle BIW application case is subsequently presented. A beam and joint layout is created, and used for a fast sensitivity analysis to identify suitable modifications to improve the global modes. Next, two application cases are presented. First, a fast optimization analysis is performed to optimize the global body modes. Subsequently, suitable physical modifications are identified and applied to the full FE model; it is shown that the effect of these physical modifications is accurately predicted with the fast sensitivity analysis.