Cost objectives

Unit specific capital cost terms Power function for capital cost objective function maximum amount of state s stored within the time horizon of interest... 

Secondly, the minimum amount of intermediate storage is determined with and without the PIS operational philosophy. In both cases the production goal was set to that which was achieved when the model was solved with infinite intermediate storage. In the illustrative example a 20% reduction in the amount of intermediate storage is achieved. The design model is an MINLP model due to the non-linear capital cost objective function. This model is applied to an illustrative problem and results in the flowsheet as well as determining the capacities of the required units. 

The second mathematical formulation presented, is a design model based on the PIS operational philosophy. This formulation is an MINLP model due to the capital cost objective function. The model is applied to a literature example and an improved design is achieved when compared to the flowsheet. The design model is then applied to an industrial case study from the phenols production facility to determine its effectiveness. The data for the case study are subject to a secrecy agreement and as such the names and details of the case study are altered. 

However, if you extend this notion to an extreme and make 100,000 production runs of one unit each (actually one unit every 315 seconds), the decision obviously is impractical, since the cost of producing 100,000 units, one unit at a time, will be exorbitant. It therefore appears that the desired operating procedure lies somewhere in between the two extremes. To arrive at some quantitative answer to this problem, first define the three operating variables that appear to be important number of units of each run (D), the number of runs per year (n), and the total number of units produced per year (Q). Then you must obtain details about the costs of operations. In so doing, a cost (objective) function and a mathematical model will be developed, as discussed later on. After obtaining a cost model, any constraints on the variables are identified, which allows selection of independent and dependent variables. 

Cell Name Final Value Reduced Cost Objective Coefficient Allowable Increase Allowable Decrease... 

In contrast to the fuel-cell stack, there is very little information available about the costs of the gas production system, the compressor-expander unit and the balance of the system (pumps, separators, etc.). Cost objectives between 15/kWel and 100/kWei have been given for the gas production system (reforming). In the next few years, it will become clear whether it is possible to reach these low-cost objectives for the gas production system, the compressor-expander unit and the balance of system. 

After assigning costs to the activity cost pools in stage 1, cost drivers are identified that are appropriate for each cost pool. Then, in stage 2, the overhead costs are allocated from each activity cost pool to cost objects (e.g., prescriptions, value-added services, and patients)... 

Costs are assigned from each activity cost pool to each cost object in proportion to its consumption of the activity. Each activity has its own cost driver. 

Direct prices do not take into account the effect a decision in one part of a plant may have on the irreversibilities in another. Marginal and shadow prices do this but are more complicated to compute. They depend upon the system of equations (and their first derivatives with respect to the variables of interest) rather than upon only the states of various zones. The mathematical description of a thermodynamic process requires the specification of a set of "equations of constraint", represented here by the set, [4>.=0]. The thermodynamic performance and stream variables are divided into two sets, state and decision variables, represented by [x.] and [y ], and each of the defining functions, [4.], is expressed in terms of these variables. If the objective function, 4, (whether it is an energy objective or a cost objective) is similarly expressed, a Lagrangian may be defined according to ... 

To start the process, the engineer defines as accurately as possible the inputs, outputs and energy and cost objective functions. Then the reference environments, both physical and economical are defined. These are not necessarily straightforward steps, as for example when dealing with high rates of... 

This example treats a simple open-cycle gas turbine for which the cost objective function, equations of constraint and costing equations are all available in analytic form. Figure 3 shows these functions along with the fixed and variable decision variables. Since the set of equations is diagonalized,... 

The development of specifications for the design and construction of a system for source densification of solid waste that will meet the established size and cost objective requires extensive knowledge of the parameters governing the densification process. 

D placement tools have to be able to optimize multiple cost objectives in addition to the traditional wire length and critical path delay. 

Based on that data, temperature was optimized in terms of an annual cost objective function (AC), considering the costs of biocatalyst (EC), utilities (UC) and equipment (RC). A summary of results is presented in Table 5.5 for biocatalyst replacement at 25% initial activity sensitivity with respect to biocatalyst replacement policy is presented as a surface of response in Eig. 5.22 (Illanes et al. 2001). 

Table 5.5 Temperature Optimization Based on a Cost-Objective Function of Multiple Staggered CPBER with Chitin-Immobilized P-Galactosidase Under Biocatalyst Replacement at 25% of Initial Activity. Operation Conditions Are Those in Table 5.3...

The sponsor and others, as appropriate, clearly articulate the purposes and expected uses of the model. The purpose and use statement provides the basis for determining the scope of the model (e.g., in terms of geographic coverage, business unit coverage, and as is vs. to be views of the enterprise). The purpose, use, and scope statements then are translated into model-development time and cost objectives for the design team. 

Many organizations still use the analysis-of-variance method to determine whether cost objectives are being met within budgeted amounts. This approach gives some indication of actual vs. planned expenditures, but because data are released months after actual events occur, it is difficult to trace how activities could have been performed better. 

The total cost—setup cost plus holding cost—per time unit is XC/Q + hQ/2, where X/Q is the number of orders placed per time unit. Note that we have ignored the variable cost, the cost for purchasing the units, since this term is independent of the decision variable Q. It is equal to cA per time unit, with c being the purchasing cost per unit. The Q that minimizes this cost objective is Q = /2XCIh, which is easily derived from setting the derivative of the cost objective (with respect to 0 to zero. The square-root order quantity is often referred to as EOQ as well. 

The above describes exactly how the so-called Q, R) model works, with R being the reorder point and Q the order size. One way to set these parameters is to let Q take the EOQ value and let R be determined by service requirements. For instance, set the value of R sufficiently large so as to ensure that the stockout probability (i.e., the probability that the on-hand inventory is zero upon a demand arrival) is limited to, say, no more thm 5%, or the fill rate (the proportion of demand that is filled from on-hand inventory) is at least 95%. (Note that in general the no-stockout probability is not equal to the fill rate.) It is also possible to set up a cost objective and then optimize it to derive the best Q and R values jointly. 

This includes a brief description of design parameters and their functions for a given product or family of products. The description may also include any special test conditions or requirements. In addition, specific customer requirements that must be met for each performance characteristic, including reliability, performance, maintainability, producibility, testability, safety, and cost objectives. 

Informal and formal trade-off analysis objectives, execution, data collection requirranmts, schedule of activities, analysis of results, and expected outcomes need to be fully defined. Each trade-off analysis is conducted for the purpose of selecting among competing alternatives to support customer needs, system effectivraiess, design-to-cost, or life cycle cost objectives within acceptable levels of risk. 

The method is universal since it can be used to jointly asses new machines and ones which have been in service for many years. Besides machine age, the cost objective function covers ... 

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