Pinch-based and disjunctive optimization for process integration of wastewater interception with mass and property constraints

In-plant interception is used to adjust the concentrations and properties of multiple wastewater streams containing pollutants and environmentally-undesirable properties. The determination of the pinch point is critical for the determination of optimum design conditions. Algebraic and graphical techniques are used to locate the pinch point. The selection of the appropriate mass separating agent(s) (MSAs) is based on thermodynamic and economic considerations. A screening procedure is applied to screen competing mass separating agents. Mathematical disjunctive programming is proposed to compare alternatives and invoke the proper models when a certain technology is to be utilized. The model minimizes the total annualized cost, which includes the cost of the selected separating agents and the annualized cost of their associated equipment (depreciation). An example is presented to show the applicability and advantages of the proposed models.     

An integrated approach to the retrofitting of mass exchange networks

 The synthesis of optimal mass exchange networks (MENs) deals with the identification of a cost-effective network of mass exchangers that preferentially transfer certain species from rich streams to lean streams. To date, MEN synthesis has dealt with grass-root design where the emphasis is on the maximization of process lean streams usage and the minimization of operating cost. Another important class of problems is the retrofit of MENs in which mass-exchange units already exist in the plant and the focus is to maximize the usage of the process units so as to minimize capital cost of newly added units and trade it off with operating cost. In this paper, we develop a systematic procedure for the retrofitting of MENs. First, we identify alternative structural configurations of interest through heuristics. Series and parallel structures are addressed. Next, we focus on two primary retrofitting strategies: those restricted by no capital constraints and those involving capital expenditure. The no-capital alternatives include enhancing performance of a current system as well as solvent substitution. The capital-based alternatives include the addition of new equipment. A new type of mass-pinch analysis is developed to maximize the utilization of existing capital while reconciling added capital with operating cost. The main concept in this novel pinch diagram is identifying maximum performance as dictated not only by thermodynamic limitations but also by physical size limitations. Different process alternatives are considered and screened to attain the optimum design. A case study is presented to demonstrate the broad applicability and potential benefits of the novel approach. Received: 30 July 2000 / Accepted: 11 October 2000     

An integrated approach to tolerance synthesis,process selection and machining parameter optimization problems

Tolerance synthesis, process selection and machining parameter optimization have been recognized as key issues to ensure product quality and reduce production cost. Although the three issues are closely interrelated, they are rarely addressed simultaneously. This often leads to inconsistent and conflicting decisions. This paper reports an integrated approach for simultaneously addressing these issues subject to their common constraints and considers both tangible and intangible cost criteria. Most commonly used machining processes such as milling, turning, drilling, reaming, boring and grinding have been taken into account. Particular attention has also been paid to multiple quality characteristics. Two example problems, one requiring rotational machining, the other involving planar machining, are solved to demonstrate the application of the proposed approach.     

An approach to multi‐start clustering for global optimization with non‐linear constraints

This paper describes a multi‐start with clustering strategy for use on constrained optimization problems. It is based on the characteristics of non‐linear constrained global optimization problems and extends a strategy previously tested on unconstrained problems. Earlier studies of multi‐start with clustering found in the literature have focused on unconstrained problems with little attention to non‐linear constrained problems. In this study, variations of multi‐start with clustering are considered including a simulated annealing or random search procedure for sampling the design domain and a quadratic programming (QP) sub‐problem used in cluster formation. The strategies are evaluated by solving 18 non‐linear mathematical problems and six engineering design problems. Numerical results show that the solution of a one‐step QP sub‐problem helps predict possible regions of attraction of local minima and can enhance robustness and effectiveness in identifying local minima without sacrificing efficiency. In comparison to other multi‐start techniques found in the literature, the strategies of this study can be attractive in terms of the number of local searches performed, the number of minima found, whether the global minimum is located, and the number of the function evaluations required. Copyright © 2002 John Wiley & Sons, Ltd.     

A dynamic programming approach to integrated assembly planning and supplier assignment with lead time constraints

As manufacturers face fierce competition in the global market, responsiveness has become an important competitiveness factor in addition to quality and cost. One essential responsiveness strategy is to reduce product development and lead times by integrating assembly planning with supplier assignment. This paper addresses the problem of integrated assembly and supply chain design under lead-time constraints by formulating and solving an optimisation problem with minimal total supply chain costs. This new time-constrained joint optimisation problem belongs to an NP-hard resource-constrained scheduling problem. To model this problem effectively, we develop a novel Hyper AND/OR graph and apply it for integrating assembly and supply chain decisions. We also develop a dynamic programming model and associated algorithm in order to solve the integrated optimisation problem with pseudo-polynomial time complexity in practice. Numerical case studies validate that the methods developed can solve the integrated decision-making problem optimally and efficiently. This paper overcomes the limitations of previous studies on concurrent assembly decomposition and supplier selection, which optimises cost without time constraints. The models and results of this research can be applied to a variety of areas including assembly design, maintenance module planning and supply chain restructuring.     

An approach to optimization with heuristic methods of scheduling

This paper describes an approach to the optimization of heuristic scheduling in batch and jobbing manufacture. The approach is based upon the use of a composite weighted priority index to resolve conflicts between operations in order to meet a predefined management objective function. The effects of combined despatching parameters in the priority index are investigated and examples are given of the resulting response surfaces. Using the techniques of harmonic analysis a model of the underlying surface trend is identified and used to predict the location of optimal schedules. Typical experimental results are presented which suggest that the proposed method compares favourably with traditional scheduling techniques.     

An iterative approach to strucural optimization

An iterative procedure of structural optimization is discussed that combines finite element analysis with the use of explicit optimality conditions. The procedure is illustrated by examples concerning sandwich beams with constraints on the deflection at a specified section, the maximum deflection or the sum of the maximum deflection in all spans of a continuous beam. The examples suggest that, starting from a uniform beam, by far the greatest saving in weight is obtained in the first two or three iterations.     

An approach to machining process optimization

Optimization is rightly claimed to be the most significant factor distinguishing the modern approach to machining processes from the orthodox one. Practical results can be obtained from the application of mathematical modelling and optimization techniques.

The paper presents a procedure for solution of machining process optimization problems, with the use of theory of graphs and Bellman's optimum principle.

The finite graph G=(N, A) (where -N denoted a set of nodes and A the set of arcs) here presents the set of feasible solutions. Each are represents a corresponding machining operation and each path the feasible machining process.

A number can be associated with each are : the increment of criterion for optimality. Using the optimum principle we can find the shortest possible path in the graph, thus solving given problems of choice for the optimal machining process.

There is a variety of ways in which the performance criterion can be formulated. In this paper only those performance measures having sufficient economical justification are considered. We may minimize the costs of machining processes, or optimize economical effectiveness of capital engaged.

The method presented can be applied with every additive criterion, as well as with some non-additive ones. A practical example illustrates the field of possible application of this method.     

An approach to computer integrated production management

A new paradigm is proposed for the realization of computer integrated production management. Computer integrated manufacturing (CIM) can never be constructed just by combining the automated devices available at present, such as CAD, CAM, CAPP and MRP systems. To realize successful CIM, the automation of friendly communication between experts is required, which plays a most important role in the integration of the various functions of production management. This points to the importance of computer integrated production management. In order to confirm the validity of the paradigm proposed in this paper, a prototype in process planning has been developed which aims at integration with CAD.     

An algorithmic approach to the optimization of process cogeneration

In most industrial processes, there is a significant need for electric power and for heating. Process cogeneration is aimed at the simultaneous provision of combined heat and power. The net result is usually a reduction in the overall cost and emissions of greenhouse gases. Therefore, there is a significant need for the optimal design of process cogeneration systems. This objective of this paper is to introduce an algorithmic approach to the optimal design of process cogeneration systems. Focus is given to the interaction of the power cycle with the process heat requirements. Because of the need for explicit thermodynamic expressions, a new set of thermodynamic correlations of steam properties is developed for proper inclusion within a mathematical-programming approach. An optimization formulation is developed to provide a generally applicable tool for integrating the process and the power cycle and for identifying the optimum equipment size, operating parameters (such as boiler pressure, superheat temperature and steam load). The objective can be chosen as minimizing the cost, satisfying the heat requirement of the process, or producing the maximum possible of power. A case study is solved to illustrate the applicability of the devised approach and associated thermodynamic correlations.     

An integrated approach to the synthesis of geometrically non-linear structures

An integrated approach to the minimum weight design of geometrically non-linear three dimensional truss structures with geometric imperfections, subject to inequality constraints on static displacements, stresses, local buckling and cross sectional areas, is investigated. The integrated structural synthesis problem involves design and response quantities as independent variables and equilibrium equations, describing the finite element model, as equality constraints. The non-linear structural analysis and the optimization are thus merged together into a single process. A computer program developed to compute the contraint values and analytical gradients is coupled with a generalized reduced gradient algorithm to solve the integrated problem. Numerical results for a geometrically non-linear shallow dome example problem are presented for various types of imperfections. Furthermore, it is found that the algorithm is capable of detecting and guarding against system as well as element elastic instability using equilibrium information only, that is, without imposing system and local buckling inequality constraints.     

An integrated approach to document decomposition and structural analysis

A document image is a visual representation of a paper document, such as a journal article page, a cover page of facsimile transmission, office correspondence, an application form, etc. Document image understanding as a research endeavor consists of developing processes for taking a document through various representations, from scanned image to semantic representation. This article describes document decomposition and structural analysis, which constitutes one of the major processes involved in document image understanding. The current state of the art and future directions in the areas of document segmentation, layout analysis, and logical block grouping are indicated. A system that performs decomposition and structural analysis (including logical grouping and read-order determination) on complex multiarticled documents is presented. This system uses bottom-up segmentation techniques to identify the block structure of a document, and layout rules to classify and group these blocks into logical units that represent meaningful subdivisions of the document. Experimental results showing the efficiency of this approach are presented and discussed. © 1996 John Wiley & Sons, Inc.     

A level set approach for topology optimization with local stress constraints

The purpose of this work is to present a level set‐based approach for the structural topology optimization problem of mass minimization submitted to local stress constraints. The main contributions are threefold. First, the inclusion of local stress constraints by means of an augmented Lagrangian approach within the level set context. Second, the proposition of a constraint procedure that accounts for a continuous activation/deactivation of a finite number of local stress constraints during the optimization sequence. Finally, the proposition of a logarithmic scaling of the level set normal velocity as an additional regularization technique in order to improve the minimization sequence. A set of benchmark tests in two dimensions achieving successful numerical results assesses the good behavior of the proposed method. In these examples, it is verified that the algorithm is able to identify stress concentrations and drive the design to a feasible local minimum. Copyright © 2014 John Wiley & Sons, Ltd.     

An integrated approach to the facilities and material handling system design

The facility layout problem involves the optimal location of manufacturing facilities into a workshop. The classical approach to the layout design is carried out in two separate steps: the first step is the construction of the block layout, i.e. the location of the departments into the workshop, and the second step is the design of the material handling system. The separate optimization of these two aspects of the problem leads to solutions that can be far from the total optimum. In this paper, an integrated approach to the facilities and material handling system design is proposed. Referring to a physical model, named the bay structure , and to a unidirectional AGV system, a genetic approach is proposed to individuate the locations of the departments, the positions of the pickup/delivery stations and the direction of the flow-path. The minimization of material handling cost is adopted as optimality criterion.     

An integrated approach to the vehicle routing and container loading problems

Real-world distribution problems raise some practical considerations that usually are not considered in a realistic way in more theoretical studies. One of these considerations is related to the vehicle capacity, not only in terms of cubic meters or weight capacity but also in terms of the cargo physical arrangements. In a distribution scene, two combinatorial optimization problems, the vehicle routing problem with time windows and the container loading problem, are inherently related to each other. This work presents a framework to integrate these two problems using two different resolution methods. The first one treats the problem in a sequential approach, while the second uses a hierarchical approach. To test the quality and efficiency of the proposed approaches, some test problems were created based on the well-known Solomon, Bischoff and Ratcliff test problems. The results of the integrated approaches are presented and compared with results of the vehicle routing problem with time windows and the container loading problem applied separately.     

Reliability-based design optimization with frequency constraints using a new safest point approach

In the reliability-based design optimization (RBDO) model, the mean values of uncertain variables are usually applied as design variables, and the cost is optimized subject to prescribed probabilistic constraints as defined by a nonlinear mathematical programming problem. Therefore, an RBDO solution that reduces the structural weight in non-critical regions provides not only an improved design, but also a higher level of confidence in the design. Solving such nested optimization problems is extremely expensive for large-scale multidisciplinary systems that are likewise computationally intensive. This article focuses on the study of a particular problem representing the failure mode of structural vibration analysis. A new method is proposed, called safest point, that can efficiently give the reliability-based optimum solution under frequency constraints, and then several probability distributions are developed, which are mathematically nonlinear functions, for the proposed method. Finally, the efficiency of the extended approach is demonstrated for probability distributions such as log-normal and uniform distributions, and its applicability to the design of structures undergoing fluid–structure interaction phenomena, especially the design process of aeroelastic structures, is also demonstrated.     

The fundamentals of work system compatibility theory: An integrated approach to optimization of human performance at work

This paper presents a general framework for the work system compatibility (WSC) theory based on two fundamental premises: (1) the synergistic effects of the entire domain of work factors upon the performance of individuals in the workplace must be considered; and (2) the work system elements must be balanced to achieve simultaneous optimization of all facets of workplace human performance measures. The WSC theory is integrative on two levels. First, the WSC theory integrates previous human performance theories that only considered the impact of some sub-sets of work factors on selected outcome measures. Secondly, the WSC theory serves to integrate prior theories towards a multi-disciplinary systems approach to work system improvements. The WSC theory provides a methodology for achieving a balance among key elements of work system by simultaneous optimization of the relevant human performance measures.     

An unconventional approach to integrated ground and surface water development

The conjunctive use of surface water with groundwater development in the Ganga Basin is considered more desirable due to unacceptable environmental conditions created by using all the low flows and the limited possibilities of surface storages. There are several ways to increase infiltration during the monsoon season. One method is to create groundwater storage by pumping during the non-monsoon period. A procedure for estimating the extent and the rate of pumping such that it is replenished in 120 days of the monsoon season and equilibrium is achieved, is outlined in this study. The areas in the Ganga Basin suitable for such groundwater storage schemes have been marked out and the economic aspects of the scheme have also been studied. It is concluded that with this scheme of underground storage of flood water the total potential irrigation in the Ganga Basin may be limited by the area of irrigable land rather than the water supply. It is suggested that this potentially advantageous scheme should be systematically studied and investigated in detail and factors like sediment transportation which may reduce the infiltration rate, the possible hazards of subsidence due to lowering of the water table, the possible ecological effects, and other relevant issues should also be considered.     

A bidirectional evolutionary structural optimization algorithm for mass minimization with multiple structural constraints

A bidirectional evolutionary structural optimization algorithm is presented, which employs integer linear programming to compute optimal solutions to topology optimization problems with the objective of mass minimization. The objective and constraint functions are linearized using Taylor's first-order approximation, thereby allowing the method to handle all types of constraints without using Lagrange multipliers or sensitivity thresholds. A relaxation of the constraint targets is performed such that only small changes in topology are allowed during a single update, thus ensuring the existence of feasible solutions. A variety of problems are solved, demonstrating the ability of the method to easily handle a number of structural constraints, including compliance, stress, buckling, frequency, and displacement. This is followed by an example with multiple structural constraints and, finally, the method is demonstrated on a wing-box, showing that topology optimization for mass minimization of real-world structures can be considered using the proposed methodology.     

An integrated group decision-making approach to quality function deployment

Quality Function Deployment (QFD) is a multi-disciplinary team process in which team member preferences are often in conflict with respect to varied individual objectives. Successful applications of QFD, thus, rely on: (1) effective communication among team members to reach a consensus; (2) assigning importance levels that reflect each individual member's preferences; and (3) mutual interaction of these two factors. No previous paper in the QFD literature has attempted to aggregate team members' opinions in the case where each individual has his or her own criteria. In this study, we consider both agreed criteria, if any, and individual criteria, simultaneously; whereas AHP, MAUT, and others are based only on an agreed set of criteria. Specifically, we modify the nominal group technique to obtain customer requirements, and integrate agreed and individual criteria methods to assign customer's importance levels in general situations where some members in a team have an agreed criteria set while others prefer individual criteria sets. By using voting and linear programming techniques, the proposed approaches consolidate individual preferences into a group consensus in situations starting with or without (partial) agreed criteria sets. This integrated group decision-making system minimizes inconsistency over group and individual preferences and provides preference ordering for alternatives through iterative communication and the resolution of any inconsistencies that exist between the group and individuals, and amongst the individuals themselves.