Showing papers in "Engineering Optimization in 1994"
TL;DR: In this paper, the optimal scheduling of a system with combined heat and power (CHP) units and a heat storage is formulated as that of minimizing the total costs over the planning period.
Abstract: The problem considered concerns the optimal scheduling of a system with combined heat and power (CHP) units and a heat storage. The purpose of the heat storage is to permit a partial decoupling of the variations in the demand for heat and electrical power. The problem of optimal scheduling is formulated as that of minimizing the total costs over the planning period. The heat demand from the district heating system and the shadow prices for the electrical power system are taken as externally given parameters. The resulting model is solved by dynamic programming. Implementation details and examples of result of the optimization are given.
43 citations
TL;DR: In this paper, the influence of actuator/sensor locations and feedback gains on the optimum design of actively controlled structures is addressed. But the authors focus on the minimization of the minimum weight structural design, while satisfying constraints on the closed loop eigenvalues and damping ratios.
Abstract: The paper deals with the influence of actuator/sensor locations and feedback gains on the optimum design of actively controlled structures. Two related problems are addressed. The first is a parametric study dealing with the effect of number and location of actuators on the minimum weight structural design, while satisfying constraints on the closed loop eigenvalues and damping ratios. The second problem addresses the optimal placement of actuators with the damping augmentation provided by the control action being used as the performance criterion. A solution methodology which allows for an integrated determination of feedback gains and actuator/sensor locations while maximizing the energy dissipated by the controller is presented. Since the actuator locations are spatially discrete whereas the feedback gains are continuous, the resulting optimization problem has mixed discrete-continuous design variables. This problem is solved using a hybrid optimization method which is a synergistic blend of artificial...
39 citations
TL;DR: In this paper, a decision-based approach to condition-based maintenance management of rotating machinery is introduced and illustrated by formulating and solving a multiple objective maintenance management problem for a 15 MW industrial gas turbine.
Abstract: A decision-based approach to condition-based maintenance management of rotating machinery is introduced and illustrated by formulating and solving a multiple objective maintenance management problem for a 15 MW industrial gas turbine. The compromise Decision Support Problem approach is used because it provides a convenient way of incorporating both information from condition monitoring and considerations of factors such as machine degradation, operating cost (fuel cost), production loss, maintenance cost, environmental protection, machine availability, etc. The focus in this paper is on explaining the approach rather than on the results per se.
19 citations
TL;DR: This paper considers the part-machine cell formation decision of the generalized Group Technology problem in which multiple process routes can be generated for each part and suggests an assignment method which is a simple linear programming.
Abstract: This paper considers the part-machine cell formation decision of the generalized Group Technology (GT) problem in which multiple process routes can be generated for each part. The existing p-median model and similarity coefficient algorithm can solve only small-sized or well-structured cases. An assignment method for the cell formation problem is suggested. This method uses an assignment model which is a simple linear programming. Numerical examples show that the assignment method provides good separable cell formation even for large-sized and ill-structured problems.
18 citations
TL;DR: In this article, a mathematical model is developed to optimally determine the product mix, replacement of old machine(s) with new machine (s) and relocation of machine(S) considering the limitations of existing resources.
Abstract: With the introduction of Flexible Manufacturing Systems, a number of factors such as machine acquisition, machine flexibility, input requirements, material handling and machine relocation influence the multiple machine replacement problem. In this paper, a mathematical model is developed to optimally determine the product mix, replacement of old machine(s) with new machine(s) and relocation of machine(s) considering the limitations of existing resources. The objective of the model is to maximize the profit. A number of example problems are solved to illustrate the application of the model and its ability to react to changes in input parameters.
6 citations
TL;DR: It is argued that the use of fuzzy set theory will generally provide models of better proximity to the systems modelled than the traditional approaches and can be taken into account by using fuzzy set notations.
Abstract: A fuzzy dynamic programming approach is proposed for finding all efficient solutions for a routing problem within a specified overall multiobjective function (e.g. overall cost, overall time, overall distance, etc). The weighting factor (parametric) approach is used to characterize efficient solutions. A characteristic feature of the present approach is that the objective function (scalarization) can be taken into account by using fuzzy set notations. By recourse to fuzzy set theory, a fuzzy dynamic programming algorithm is developed for a routing problem. It is argued that the use of fuzzy set theory will generally provide models of better proximity to the systems modelled than the traditional approaches. The effectiveness of the proposed approach is demonstrated by a numerical example.
6 citations
TL;DR: In this article, a multidisciplinary optimization procedure is developed for the design of high speed proprotors to simultaneously maximize the propulsive efficiency in high speed cruise and the rotor figure of merit in hover.
Abstract: A multidisciplinary optimization procedure is developed for the design of high speed proprotors. The objectives are to simultaneously maximize the propulsive efficiency in high speed cruise and the rotor figure of merit in hover. Since the problem involves multiple design objectives, multiobjective function formulation techniques are used. Two different multiobjective function procedures, the Kreisselmeier-Steinhauser function approach and the Minimum Sum β approach, are used. A detailed two-celled isotropic box beam is used to model the load carrying member within the rotor blade. Constraints are imposed on rotor blade aeroelastic stability in cruise, the first natural frequency in hover and total blade weight. Both aerodynamic and structural design variables are used. The results obtained using both objective function formulations are compared lo the reference rotor and show significant aerodynamic performance improvements without sacrificing dynamic and aeroelastic stability characteristics. The proced...
5 citations
TL;DR: Numerical results show that SQR as devised in this paper is the best method as far as robustness and speed of convergence are concerned in solving general constrained optimization problems.
Abstract: Some recent studies indicate that the sequential quadratic programming (SQP) approach has a sound theoretical basis and promising empirical results for solving general constrained optimization problems. This paper presents a variant of the SQP method which utilizes QR matrix factorization to solve the quadratic programming subproblem which result from taking a quadratic approximation of the original problem. Theoretically, the QR factorization method is more robust and computationally efficient in solving quadratic programs. To demonstrate the validity of this variant, a computer program named SQR is coded in Fortran to solve twenty-eight test problems. By comparing with three other algorithms: one multiplier method, one GRG-type method, and another SQP-type method, the numerical results show that, in general, SQR as devised in this paper is the best method as far as robustness and speed of convergence are concerned in solving general constrained optimization problems.
5 citations
TL;DR: In this article, a product mix problem (PMP) for cellular manufacturing systems is formulated and a polynomial time algorithm to solve a special case of the PMP is developed.
Abstract: The ability of modern manufacturing systems to be operated profitably at different output levels (volume flexibility) is one of their advantages With volume flexibility, the decision maker must decide on time capacity allocation among products and the throughput of the manufacturing system for each When sufficient time capacity to produce at throughputs that minimize unit costs exists, the problem is solved by doing so The problem is more difficult when time capacity is insufficient to produce at throughputs resulting in minimum unit costs In this paper, a product mix problem (PMP) for cellular manufacturing systems is formulated The decision variables of the PMP are: a) the time capacity to allocate to each product, and b) the throughput of the manufacturing cell for each product A polynomial time algorithm to solve a special case of the PMP is developed and the results are illustrated with numerical examples
3 citations
TL;DR: In this paper, the design of power system shunt filters to ensure harmonic reduction and noise mitigation on the electrical utility grid is formulated as an optimization problem based on the minimization of the L ∞-norm, over a specified continuous interfering frequency range, of a composite user specified objective function depicting the three main filter objectives.
Abstract: In this paper the design of power system shunt filters to ensure harmonic reduction and noise mitigation on the electrical utility grid is formulated as an optimization problem. The proposed filter design technique ensures the most economic filter design, and deviates from the common design practise of dedicating specific filters to designated harmonic interfering orders. It is based on the minimization of the L ∞-norm, over a specified continuous interfering frequency range, of a composite user specified objective function depicting the three main filter objectives of low harmonic injection into the AC host utility grid, maximum absorption by the harmonic filter and minimum harmonic voltage distortion at the point of common coupling (PCC). In addition to these objectives, near parallel resonance conditions on the combined system/filter configuration are to be avoided. These conditions are included in the formulation of the optimization problem as a functional inequality constraint over the speci...
3 citations
TL;DR: In this paper, the optimal design of reinforced concrete structures, subjected to variable and repeated loads, is studied in the shape of quadratic constraints, by the so-called perturbation method.
Abstract: Structures subjected to variable repeated loads can undergo the shakedown or adaptation phenomenon,-which prevents them from collapse but may cause lack of serviceability, for the plastic deformations developed, although finite, as shakedown occurrence postulates, may exceed some maximum values imposed by external ductility criteria. This paper is devoted to the optimal design of reinforced concrete structures, subjected to variable and repeated loads. For such structures the knowledge of the actual values taken by the plastic deformations, at shakedown occurrence, is a crucial issue. An approximate assessment of such plastic deformations is needed, which is herein provided in the shape of quadratic constraints, by the so-called perturbation method. By suitable finite element discretization, the optimal shakedown problem is formulated as a convex nonlinear mathematical programming one. The M-N (bending moment-axial force) interaction is accounted for in the aim to provide the optimal shakedown design. The...
TL;DR: The combined kinematic and dynamic synthesis of a four bar linkage, a classic example in mechanical engineering that involves both imprecise and stochastic uncertainty, is presented and a fuzzy compromise DSP involving fuzzy membership functions is used to model imprecising information.
Abstract: The early stages of design are often characterized by uncertainty. However, important design decisions are made in these stages in the presence of uncertainly. Fuzzy and Bayesian compromise Decision Support Problems (DSPs) are found to be effective in modelling this uncertainty and making decisions in such situations: In this paper, the combined kinematic and dynamic synthesis of a four bar linkage, a classic example in mechanical engineering that involves both imprecise and stochastic uncertainty, is presented. A fuzzy compromise DSP involving fuzzy membership functions is used to.model imprecise information. Stochastic uncertainty is modelled by a Bayesian compromise DSP using Gaussian distributions. The crisp formulation (ignoring uncertainty) is presented first, followed by the fuzzy and Bayesian formulations. The results of the various models and their validation are also presented. A comparison is made between the information obtained from the crisp, fuzzy and Bayesian formulations by perfo...
TL;DR: The key concept is an integrated model that can concurrently handle all of the related design and construction disciplines in the decision making process that is decomposed hierarchically into several subproblems, thus a multilevel multiobjective optimization problem is obtained.
Abstract: In this paper, an optimization-based design model of precast concrete wall panels ( PCWP) for a building facade is presented. The key concept is an integrated model that can concurrently handle all of the related design and construction disciplines in the decision making process. The integrated model is decomposed hierarchically into several subproblems, thus a multilevel multiobjective optimization problem is obtained. Besides the multilevel aspect, the model presented can also handle knowledge-based requirements which are in general difficult to deal with by conventional hill-climbing optimization schemes. A solution procedure to solve this model is developed and applied to an example of PCWP for a four-story building facade.
TL;DR: In this paper, a numerical algorithm for simultaneous optimization of control and structural systems is proposed, analyzed and evaluated in a sequence, where the structural and control design subproblems are solved in the sequence.
Abstract: A numerical algorithm for simultaneous optimization of control and structural systems is proposed, analyzed and evaluated in this paper. In the procedure, the structural and control design subproblems are solved in a sequence. In the outer loop, it is proposed to solve the constrained structural optimization problem using the nonlinear programming ( NLP) approach, and in the inner loop, the control design problem is proposed to be solved using the differential dynamic programming ( DDP) approach. For the optimal control design problem, the functional and pointwise state variable constraints are treated using the augmented Lagrangian approach. The resulting unconstrained control design subproblem is then solved using the DDP approach which has been determined to be more efficient than the NLP approach for this class of problems. The basic ideas of the augmented Lagrangian and the DDP approaches are explained. The proposed approach is quite general as it can treat linear as well as nonlinear system...
TL;DR: A heuristic is developed for determining effective assembly sequences for mixed-model assembly lines that produce products with different part requirements in a JIT manufacturing environment that is modified to solve the assembly sequencing problem considered in Toyota.
Abstract: Effective assembly sequence is essential to production smoothing for Just-in-Time (JIT) manufacturing. In this paper, a heuristic is developed for determining effective assembly sequences for mixed-model assembly lines that produce products with different part requirements in a JIT manufacturing environment. The objective is to maintain a constant rate of usage for every part consumed by the line. A numerical example is used to illustrate the procedure of the heuristic. The performance of the heuristic is then examined by using randomly generated test problems. In addition, the heuristic developed is modified to solve the assembly sequencing problem considered in Toyota.
TL;DR: In this paper, a rigorous simulation-based analysis of the Dynamic Chiller Sequencing (DCS) strategy for controlling HVAC equipment is presented, where the effects of many factors affecting the cooling load in a building as well as several parameters of the DCS procedure have been systematically explored to identify those which have the greatest impact on DCS performance.
Abstract: This paper presents a rigorous simulation-based analysis of the Dynamic Chiller Sequencing (DCS) strategy for controlling HVAC equipment. The effects of many factors affecting the cooling load in a building as well as several parameters of the DCS procedure have been systematically explored to identify those which have the greatest impact on DCS performance. The ability of DCS to reduce energy costs relative to heuristic strategies typical of those found in conventional building control systems is also assessed.
TL;DR: Criteria for efficient and optimal design of thermal systems are presented and a two-level design structure is introduced to enable the designer to adapt his design to the available technology level, type of application, economic factors, and O&M requirements.
Abstract: In this paper, criteria for efficient and optimal design of thermal systems are presented. The main emphasis of the paper is in the problem set-up and in the structuring of the thermal system design information during the conceptual design phase. A two-level design structure (macro-level and micro-level) is introduced to enable the designer to adapt his design to the available (or required) technology level, type of application, economic factors, and O&M requirements. At the macro-level of design, economic feasibility (business) decisions are made, while at the micro-level of design, technical feasibility (engineering) decisions are made. A 50 MW wood burning power plant in Northern California is presented as an illustrative case study. All the information provided in the paper is from real world power plant design, and the problem is presented in a form to allow other researchers to try different optimization techniques to solve the problem.
TL;DR: In this paper, a scheduling problem at a bottleneck common facility for nsubsequent production lines, each of which is dedicated to produce a family of products, is dealt with, where the common facility represents the bottleneck, since its capacity is less than the sum of the capacities of the n production lines.
Abstract: This paper deals with a scheduling problem at a bottleneck common facility for nsubsequent production lines, each of which is dedicated to produce a family of products. The common facility represents the bottleneck, since its capacity is less than the sum of the capacities of the n production lines. The components supplied by the bottleneck for the n lines are not exactly the same, and hence a non-productive change-over (or setup) time for the bottleneck is incurred when jobs switch between families. As such, it is desirable to make as few change-overs as possible to save the expensive setup time. However, if the bottleneck continues processingjobs for a given line, not only will the inventory at the line build up but also other lines will become idle. Thus, a scheduling scheme must be developed for finding a schedule that keeps alt the production lines busy with few change-overs for the bottleneck. This objective can be appropriately measured by minimization of the total production time. For the...
TL;DR: In this article, the optimal repair-cost limits for a Weibull-distributed time to failure and an exponentially distributed repair cost were derived for the case where the repair cost minimizes the average cost per unit time for repairs and replacement.
Abstract: This paper examines optimal repair-cost limits for a Weibull-distributed time to failure and an exponentially distributed repair cost. Bounds are derived for the optimal repair cost limit that minimizes the average cost per unit time for repairs and replacement. With those bounds, a simple algorithm is developed to obtain the optimal repair-cost limit. Numerical examples are given to illustrate the algorithm.
TL;DR: In this paper, a nonlinear mixed zero-one integer programming problem aimed to maximize total output by scheduling the operational time of N non-identical machines is formulated and solved.
Abstract: The purpose of this paper is to formulate and solve a nonlinear mixed zero-one integer programming problem aimed to maximize total output by scheduling the operational time of N non-identical machines. Properties of the optimal solution are identified under restrictions imposed on machine availability and various budget constraints. A branch and bound algorithm to solve the problem is suggested.