Assignment 10b: NIMBY!

Pan TC, Kao JJ (2009) GA-QP Model to Optimize Sewer System Design, JOURNAL OF ENVIRONMENTAL ENGINEERING, 135(1) 17-24

Summary

Sanitary sewers aren’t rocket science. Upstream elevations must be greater than downstream elevations. The diameters of downstream pipes must be larger than their upstream counterparts. A line must be sufficiently large to carry a design flow. These are usually the main concerns, which are often accompanied by other sets of secondary limitations. If viewed at the level of an individual sewer line, its optimal design is a fairly simple problem to solve. When optimizing the sewer design for a large network, however, the process becomes exceedingly complex. In this study, the authors attempted to tackle the latter.

The problem in this article was so complex, in fact, that the authors had to break the optimization process into two separate parts: a genetic algorithm and a quadratic program. In the genetic algorithm, a set of pipe diameters for the entire system constituted a chromosome of possible solutions. These chromosomes were then passed to the quadratic program, in which the cost was optimized by modifying pipe slopes and buried depths. Optimal solutions in the quadratic program were limited by an array of constraints commonly encountered in sewer design. The result of the quadratic program was then fed back to the genetic algorithm, where the fitness of a chromosome was evaluated as the inverse of its cost (as cost increased, the fitness of a chromosome became worse, and vice versa). Upon running the GA-QP model, results were fed into an MGA function, which was used to save “good alternative” solutions which were not mathematically optimal. When applied to a case study, the authors’ method was successful in reducing the cost of a sewer design from $87 million to $10 million – a reduction of nearly 90%.

Discussion

This article was an interesting implementation of a GA, but I found two major setbacks.

First and foremost, I feel that the authors’ exclusion of particular design factors and “unquantifiable issues” would render any optimal or near-optimal solution infeasible. Geology is a major factor in any project involving cut and fill, and can cause unexpected changes in design in order to minimize costs. Although the inclusion of “unquantifiable issues” is nearly impossible in a model, I feel that the constraints posed by these issues would result in a significantly more expensive final design than what the authors advertise.

Secondly, I feel that the authors’ method is fairly limited in applicability. In order for this GA-QP scheme to be implemented, a new, large sewer network must be installed at a single point in time. New residential neighborhoods are obviously a good application, but the method offers no suggestions of improvement to existing networks, or small expansions upon such networks.

Nevertheless, I found the authors’ ideas to be interesting and worthwhile. Even if real-world constraints reject optimal and near-optimal solutions generated by the model, these solutions may encourage new approaches to design which could potentially save millions.

Assignment 10a: Brills, Brills, Brills

Brill E.D. (1979) USE OF OPTIMIZATION MODELS IN PUBLIC-SECTOR PLANNING, MANAGEMENT SCIENCE, 25

Summary

Brill’s article returns to a concept which we discussed near the beginning of this semester: “wicked” problems of the public sector, and how optimization models should be adapted when applied to these types of situations.

Brill begins his article by outlining the limitations of using optimization models. He points out how the economic efficiency objective is insufficient on two fronts: (1) it neglects to consider equity, and (2) it has empirical shortcomings associated with estimating benefits and costs. With respect to complete multiobjective models, Brill notes that in problems with several objective functions it may be “computationally impractical to generate a complete set of trade-off relationships.” He also observes that these complex problems may have “a plethora of local optima,” and that it would be impractical to have decision maker participate in the process. With incomplete models, Brill points out that the best solution may lie in the inferior region, since certain objectives are ignored.

With these shortcomings in mind, Brill suggests that “a philosophy of using optimization to aid the planning process” be adopted. This is in contrast to many current applications, in which complete “answers” are sought. Brill offers many suggestions which would streamline optimization models with the traditional “planning process.” His first set of suggestions involve the joint use of models, which he claims would enhance the capabilities of individual models. Second, and most importantly, Brill argues for the “use of optimization models to generate alternatives and facilitate evaluations.” He believes that use of optimization models in this fashion would serve as catalysts for human innovation, thereby enhancing the public-sector planning process.

Discussion

I thought this article was both soft and derivative. Its concepts and construction were nearly identical to Liebman’s article which we read at the beginning of the semester. If I had to applaud the article for one idea, I would say that its “suggestions” are an improvement over those presented by Liebman in 1976. Liebman’s “simple-minded suggestions” were extremely generic, whereas Brill’s suggestions point to specific actions which could be implemented to enhance the use of models in the planning process.

Assignment 9

Shiau JT, Wu FC (2006) Compromise programming methodology for determining instream flow under multiobjective water allocation criteria, JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 42(5), pp. 1179-1191.

Summary

The two competing objectives at the heart of this study are the consumptive use of water and environmental concern.

The Kaoping River is a major river of Taiwan, flowing southward for 171 kilometers before discharging into the South China Sea. Water uses along the Kaoping have traditionally been agricultural, but in 1999 a diversion weir was constructed with the intent of diverting 35 cms for municipal uses. The river is also the habitat for several native species of fish. Prior to this study, minimum streamflows were set at a value of 9.5 cms.

It is now well-established that natural flow variability is essential to the well-being of a river ecosystem. In order to quantify the impact of the diversion weir, the authors examined "pre-diversion" and "post-diversion" stream data (upstream and downstream of the weir, respectively). 32 specific parameters, collectively known as Indicators of Hydrologic Alteration (IHAs), were measured for each set of stream data. Weir operations were targeted to have IHAs fall within the 25th and 75th percentile of prediversion values. Based on how closely an IHA fell to this target range, a degree of hydrologic alteration was determined. Finally, using a set of formulas constructed by the authors, an overall degree of hydrologic alteration was calculated based on the 32 individual degrees of hydrologic alteration for each IHA. Minimization of the overall degree of hydrologic alteration represented the "environmental" side of this problem.

The other two objectives of concern in this study were the minimization of agricultural water shortages and municipal water shortages. These two objectives obviously encompassed the "consumptive" side of the problem. The ultimate goal of the study was the minimization of three objectives: overall degree of hydrologic alteration, minimization of agricultural shortage, and minimization of municipal shortage.

The relationships between these objectives were fairly complex, but can be summarized fairly simply - higher streamflows are better for river ecology, but increase the risk of water shortages, and vice versa. The authors ultimately found that, with equal weight applied to natural flow variability and water supply reliability, a release rate of 26 cms from the diversion weir was optimal. The authors' solution also revealed that the status quo release rate of 9.5 cms was woefully inadequate, and only provided "a modest mitigation of hydrologic alterations."

Discussion

I found this article to be one of the most interesting of what we have read this semester. I really like the practical aspect of multi-objective programming, since in reality every complex situation has competing interests and goals. One of my main problems with the article was the way in which the overall degree of hydrologic alteration was calculated (Eqns. 2a, 2b, and 2c). With the way these equations were constructed, I felt the penalty for one IHA being of moderate or high alteration was too high. In addition, I found the equal weighting of the natural flow variability and water supply objectives in the final solution to be unrealistic. Based on traditional prioritization, it would seem more accurate to assume that municipal use would have the highest priority, agricultural use would be second, and environmental concerns would be third. A solution with this type of weighting would have been more meaningful, in my opinion.