Robust solutions

This approach is proposed by Chen/Lee (2004) to reach more robust solutions considering probabilistic for in this case demand quantity scenarios without considering price uncertainty. 

The robust solution in this case will also be attainable by a controller of the form... 

This chapter has focused on formulating the context for Eq. (2) and demonstrating that a solution exists. The results to date show that a genuine and robust solution to Eq. (2) is available in the absence of a priori information. The solution, BTEM, is a very powerful tool in the investigation of homogeneous catalytic systems using in situ spectroscopies. 

It is desirable to demonstrate that the proposed stochastic formulations provide robust results. According to Mulvey, Vanderbei, and Zenios (1995), a robust solution remains close to optimality for all scenarios of the input data while a robust model remains almost feasible for all the data of the scenarios. In refinery planning, model robustness or model feasibility is as essential as solution optimality. For example, in mitigating demand uncertainty, model feasibility is represented by an optimal solution that has almost no shortfalls or surpluses in production. A trade-off exists... 

Considering risk in terms of variations in both projected benefits and recourse variables provided a more robust analysis of the problem. As explained earlier, the problem will have a more robust solution as the results will remain close to optimal for all given scenarios through minimizing the variations of the projected benefit. On the other hand, the model will be more robust as minimizing the variations in the recourse variables leads to a model that is almost feasible for all the scenarios... 

When motivation became the object of scientific study, the same kind of exceptions to rational choice soon became apparent. Pavlov came up with the most robust solution—conditioned behavior, refined to conditioned motives, stated definitively in . H. Mowrer s two-factor theory (1947).1 In this form, Plato s passions seemed discernible in parametric research, and the ancient dual model was perpetuated. 

A more robust solution is to introduce a load balancer between die clients and a farm of identical middle tier servers. The load balancer routes requests to one of the middle tier servers based on the load and netweork topology. If one middle tier server fails, it can reroute the request to another to prevent single point of failure (fail-over). This architecture requires that the servers in the middle tier farm synchronize user sessions with each other in case one has to take over a client from another. 

One aspect becoming increasingly important is the robustness of the network configuration (cf. Goetschalckx and Fleischmann 2005, p. 118). One way of establishing a robust solution is to perform sensitivity or scenario analyses on major influencing factors such as demand expectations... 

XML technologies [22, 23] have become a general standard for storing and converting all kinds of data and technically more robust solutions than mmCif based on XML, such as PROXIML [24], were proposed but still not accepted by the Research Collaboratory for Structural Bioinformatics. 

As stated above, forum participants were divided into three groups, and each group was assigned one of the three policy approaches for consideration. The purpose of the exercise was to compare the approaches and determine if one of them is more robust for some scenarios and some outcomes than others. A robust solution is one that has few if any downside risks or negative impacts as it applies to all scenarios and outcomes. Approaches that have some serious downsides are not as robust as those that minimize the negative outcomes. 

The moderate policy approach could be the most robust if one believes that the moderate policy actions would move California and the nation far enough toward the direction of increased use of hydrogen to alleviate potential problems should the big-problem scenario emerge. However, if one believes that those actions will not be enough to avoid big problems, then this scenario is not a robust solution. 

As described in Section 1.1, the goal of the simulation study is to quantify the relationships between the simulation outputs and the inputs or factors. For this case study, the outputs are the steady-state mean costs of the whole supply chain (discussed in Section 3.2) and the inputs are factors such as lead-time, quality, operation time of an individual process, and number of resources. Our ultimate goal (as reported by Kleijnen et al., 2003) is to find robust solutions for the supply chain problem. Thus we distinguish between two types of factors ... 

Kleijnen, J.P.C., Bettonvil, B., and Persson, F. (2003). Robust solutions for supply chain management Simulation, optimization, and risk analysis. http //ccnlcr.kLib.nl/slafT/klcijncn/papcrs.hlml. 

It must be noticed the cascade interconnection between the algebraic and the differential items. At each time t, the two algebraic equations system admits a unique and robust solution for in any motion in which S (the Jacobian matrix of ( ) is nonsingular for S 0). Feeding the solution into the differential equation, the following differential estimator, driven by the output and the input signals u, is obtained ... 

A few PPIs that have drawn the attention of academic and industrial research groups do not fit so easily into either of the groups surveyed in the above two sections. Evolution tends to converge on certain robust solutions to various problems, so it should come as no surprise that the central binding motifs of many PPIs tend to fall into a small number of categories. Still, there is no a priori reason why an endogenous PPI must take on any specific form. The following... 

The block of inter-linked columns offers robust simulation of a combination of complex distillation columns, as heat-integrated columns, air separation system, absorber/stripper devices, extractive distillation with solvent recycle, fractionator/quench tower, etc. Because sequential solution of inter-linked columns could arise convergence problems, a more robust solution is obtained by the simultaneous solution of the assembly of modelling equations of different columns. 

FIG. 2. A bow-tie system in which a highly conserved core process is flanked by flexible external domains provides a robust solution for dealing with a high degree of complexity. This has been used to model biological networks, including metabolism and, more recently, the immune system. (Adapted from Csete Doyle 2004.)... 

Budd PM, Ghanem BS, Makhseed S, McKeown NB, Msayib KJ, Tattershall CE. Polymers of intrinsic microporosity (PIMs) Robust, solution-processable, organic nanoporous... 

NMR has addressed the solution structures of Tm. 77, and /y Fds. Robust solution molecular models have been reported for and T/ 4Fe Fds, the... 

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