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At least 19 records

Pareto solutions in multicriteria optimization under uncertainty

We present and analyze several definitions of Pareto optimality for multicriteria optimization or decision problems with uncertainty primarily in their objective function values. In comparison to related notions of Pareto robustness, we first provide a full characterization of an alternative efficient set hierarchy that is based on six different ordering relations both with respect to the multiple objectives and a possibly finite, countably infinite or uncountable number of scenarios. We then establish several scalarization results for the generation of the corresponding efficient points using generalized weighted-sum and epsilon-constraint techniques. Finally, we leverage these scalarization results to also derive more general conditions for the existence of efficient points in each of the corresponding optimality classes, under suitable assumptions.

97 MATHEMATICS AND COMPUTING↗

SU-F-T-209: Multicriteria Optimization Algorithm for Intensity Modulated Radiation Therapy Using Pencil Proton Beam Scanning

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatment planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.

60 APPLIED LIFE SCIENCES↗

MO-FG-CAMPUS-TeP2-02: First Experiences and Perspectives in Using Direct Multicriteria Optimization (MCO) On Volumetric-Modulated Arc Therapy (VMAT) for Head and Neck Cancer

Purpose: To report the first experiences and perspectives in using direct multicriteria optimization (MCO) on volumetric-modulated arc therapy (VMAT) for head and neck (H&N) cancer. Methods: Ten prior patients with tumors in representative H&N regions were selected to evaluate direct MCO-VMAT in RayStation v5.0 beta. The patients were previously treated by intensity-modulated radiation therapy (IMRT) with MCO on an Elekta linear accelerator with Agility multileaf collimator. To avoid radiating eyes and shoulders, MCO-VMAT required one to three partial-arc groups, with each group consisting of single or dual arcs. All MCO-VMAT plans were approved by a radiation oncologist. The MCO-VMAT and MCO-IMRT plans were compared using V{sub 100}, D{sub 5}, homogeneity index (HI) and conformity index (CI) for planning target volume (PTV), D{sub mean} and D{sub 50} for six parallel organs and D{sub max} for five serial organs. Patient-specific quality assurance (QA) was performed using ArcCHECK for MCO-VMAT and Matrixx for MCO-IMRT with results analyzed using gamma criteria of 3%/3mm. Results: MCO-VMAT provided better V{sub 100} (+0.8%) lower D{sub 5}(− 0.3 Gy), lower HI (−0.27) and comparable CI (+0.05). MCO-VMAT decreased D{sub mean} and D{sub 50} for multiple parallel organs in seven of the ten patients. On average the reduction ranged from 2.1 (larynx) to 7.6 Gy (esophagus). For the nasal cavity and nasopharynx plans significant reduction in D{sub max} was observed for optics (up to 11 Gy) brainstem (6.4 Gy), cord (2.1 Gy) and mandible (6.7 Gy). All MCO-VMAT and -IMRT plans passed clinical QA. MCO-VMAT required slightly longer planning time due to the more complex VMAT optimization. The net beam-on time for the MCO-VMAT plans ranged from 80 to 242 seconds, up to 9 minutes shorter than MCO-IMRT. Conclusion: With similar target coverage, reduced organ dose, comparable planning time, and significantly faster treatment, MCO-VMAT is very likely to become the modality of choice in RayStation v5.0 for H&N cancer.

60 APPLIED LIFE SCIENCES↗

Design of vibration isolation systems using multiobjective optimization techniques

The design of vibration isolation systems is considered using multicriteria optimization techniques. The integrated values of the square of the force transmitted to the main mass and the square of the relative displacement between the main mass and the base are taken as the performance indices. The design of a three degrees-of-freedom isolation system with an exponentially decaying type of base disturbance is considered for illustration. Numerical results are obtained using the global criterion, utility function, bounded objective, lexicographic, goal programming, goal attainment and game theory methods. It is found that the game theory approach is superior in finding a better optimum solution with proper balance of the various objective functions.

Rao, S. S.↗

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system

Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Novel Approach to Postmastectomy Radiation Therapy Using Scanned Proton Beams

Purpose: Postmastectomy radiation therapy (PMRT), currently offered at Massachusetts General Hospital, uses proton pencil beam scanning (PBS) with intensity modulation, achieving complete target coverage of the chest wall and all nodal regions and reduced dose to the cardiac structures. This work presents the current methodology for such treatment and the ongoing effort for its improvements. Methods and Materials: A single PBS field is optimized to ensure appropriate target coverage and heart/lung sparing, using an in–house-developed proton planning system with the capability of multicriteria optimization. The dose to the chest wall skin is controlled as a separate objective in the optimization. Surface imaging is used for setup because it is a suitable surrogate for superficial target volumes. In order to minimize the effect of beam range uncertainties, the relative proton stopping power ratio of the material in breast implants was determined through separate measurements. Phantom measurements were also made to validate the accuracy of skin dose calculation in the treatment planning system. Additionally, the treatment planning robustness was evaluated relative to setup perturbations and patient breathing motion. Results: PBS PMRT planning resulted in appropriate target coverage and organ sparing, comparable to treatments by passive scattering (PS) beams but much improved in nodal coverage and cardiac sparing compared to conventional treatments by photon/electron beams. The overall treatment time was much shorter than PS and also shorter than conventional photon/electron treatment. The accuracy of the skin dose calculation by the planning system was within ±2%. The treatment was shown to be adequately robust relative to both setup uncertainties and patient breathing motion, resulting in clinically satisfying dose distributions. Conclusions: More than 25 PMRT patients have been successfully treated at Massachusetts General Hospital by using single-PBS fields. The methodology and robustness of both the setup and the treatment have been discussed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams

Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.

Accelerators & storage rings↗

Monaco treatment planning system tools and optimization processes

The Monaco treatment planning system combines Monte Carlo dose calculation accuracy with robust optimization tools to provide high-quality radiotherapy treatment plans for three-dimensional conformal radiotherapy (3D CRT), intensity modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), stereotactic radiosurgery (SRS), and stereotactic body radiotherapy (SBRT). Recent technology advances have allowed for fast calculation speeds, which allow clinicians and patients to benefit from the accuracy of the Monte Carlo algorithm while reducing overall planning time. A collection of biological and physical dose-based planning tools and templates simplify the planning process and allow for consistent results across organizations. At the same time, multicriteria optimization (MCO) ensures critical organs are spared to the greatest possible degree while maintaining target coverage. Monaco encompasses a full suite of treatment modalities, including conventional radiotherapy and particle therapy, and is paving the way for real-time adaptive treatments with developments in magnetic resonance (MR)-guided radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-T-344: Commissioning Constant Dose Rate VMAT in the Raystation Treatment Planning System for a Varian Clinac IX

Purpose: To demonstrate the commissioning of constant dose rate volumetric modulated arc therapy (VMAT) in the Raystation treatment planning system for a Varian Clinac iX with Exact couch. Methods: Constant dose rate (CDR) VMAT is an option in the Raystation treatment planning system, enabling VMAT delivery on Varian linacs without a RapidArc upgrade. Raystation 4.7 was used to commission CDR-VMAT for a Varian Clinac iX. Raystation arc model parameters were selected to match machine deliverability characteristics. A Varian Exact couch model was added to Raystation 4.7 and commissioned for use in VMAT optimization. CDR-VMAT commissioning checks were performed on the linac, including patient-specific QA measurements for 10 test patients using both the ArcCHECK from Sun Nuclear Corporation and COMPASS from IBA Dosimetry. Multi-criteria optimization (MCO) in Raystation was used for CDR-VMAT planning. Results: Raystation 4.7 generated clinically acceptable and deliverable CDR-VMAT plans for the Varian Clinac. VMAT plans were optimized including a model of the Exact couch with both rails in the out positions. CDR-VMAT plans generated with MCO in Raystation were dosimetrically comparable to Raystation MCO-generated IMRT plans. Patient-specific QA measurements with the ArcCHECK on the couch showed good agreement with the treatment planning system prediction. Patient-specific, structure-specific, multi-statistical parameter 3D QA measurements with gantry-mounted COMPASS also showed good agreement. Conclusion: Constant dose rate VMAT was successfully modeled in Raystation 4.7 for a Varian Clinac iX, and Raystation’s multicriteria optimization generated constant dose rate VMAT plans which were deliverable and dosimetrically comparable to IMRT plans.

60 APPLIED LIFE SCIENCES↗

RayStation: External beam treatment planning system

RaySearch Laboratories is a world leader in the field of advanced software and creator of the RayStation treatment planning system for radiation therapy. The aim with RayStation is to deliver an unmatched user experience and leading functionality. Unique features described here include multiatlas based autosegmentation for contouring, deformable registration with 2 different algorithms, multicriteria optimization, Plan Explorer, fallback planning, ultrafast computation speed, and 4-dimensional (4D) adaptive radiation therapy. RayStation can be used to plan for electrons and photons on traditional linacs, for protons on various delivery systems, and for Accuray's helical TomoTherapy system. This paper describes some of these modalities, with reference to clinical cases and including descriptions of the impact on workflow.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Investigation on High-κ Dielectric for Low Leakage AlGaN/GaN MIS-HEMT Device, Using Material Selection Methodologies

This paper analyzes various high-κ dielectrics for low leakage AlGaN (Aluminium Gallium Nitride)/GaN (Gallium Nitride) MIS-HEMT (Metal Insulator Semiconductor—High Electron Mobility Transistor) device. The investigation is carried out by examining different attributes such as the dielectric constant, conduction band offset, and energy band gap of the dielectric which are crucial for a good dielectric-AlGaN interface. This work also computes the values of band offsets of different dielectrics to AlGaN analytically. The selection of the most promising dielectric is done using three different multi-criteria decision making methods (MCDM) namely the Ashby, VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning Multicriteria Optimization and Compromise Solution) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). All the analyses point to La{sub 2}O{sub 3} as the best gate dielectric for AlGaN/GaN MIS-HEMT device.

36 MATERIALS SCIENCE↗

Projections onto the Pareto surface in multicriteria radiation therapy optimization

Purpose: To eliminate or reduce the error to Pareto optimality that arises in Pareto surface navigation when the Pareto surface is approximated by a small number of plans. Methods: The authors propose to project the navigated plan onto the Pareto surface as a postprocessing step to the navigation. The projection attempts to find a Pareto optimal plan that is at least as good as or better than the initial navigated plan with respect to all objective functions. An augmented form of projection is also suggested where dose–volume histogram constraints are used to prevent that the projection causes a violation of some clinical goal. The projections were evaluated with respect to planning for intensity modulated radiation therapy delivered by step-and-shoot and sliding window and spot-scanned intensity modulated proton therapy. Retrospective plans were generated for a prostate and a head and neck case. Results: The projections led to improved dose conformity and better sparing of organs at risk (OARs) for all three delivery techniques and both patient cases. The mean dose to OARs decreased by 3.1 Gy on average for the unconstrained form of the projection and by 2.0 Gy on average when dose–volume histogram constraints were used. No consistent improvements in target homogeneity were observed. Conclusions: There are situations when Pareto navigation leaves room for improvement in OAR sparing and dose conformity, for example, if the approximation of the Pareto surface is coarse or the problem formulation has too permissive constraints. A projection onto the Pareto surface can identify an inaccurate Pareto surface representation and, if necessary, improve the quality of the navigated plan.

60 APPLIED LIFE SCIENCES↗

A Multiobjective Optimization Framework for Stochastic Control of Complex Systems

This paper addresses the problem of minimizing the long-run expected average cost of a complex system consisting of subsystems that interact with each other and the environment. We treat the stochastic control problem as a multiobjective optimization problem of the one-stage expected costs of the subsystems, and we show that the control policy yielding the Pareto optimal solution is an optimal control policy that minimizes the average cost criterion for the entire system. For practical situations with constraints consistent to those we study here, our results imply that the Pareto control policy may be of value in deriving online an optimal control policy in complex systems.

Complex systems↗

Technical Note: Improving the VMERGE treatment planning algorithm for rotational radiotherapy

Purpose: The authors revisit the VMERGE treatment planning algorithm by Craft et al. [“Multicriteria VMAT optimization,” Med. Phys. 39, 686–696 (2012)] for arc therapy planning and propose two changes to the method that are aimed at improving the achieved trade-off between treatment time and plan quality at little additional planning time cost, while retaining other desirable properties of the original algorithm. Methods: The original VMERGE algorithm first computes an “ideal,” high quality but also highly time consuming treatment plan that irradiates the patient from all possible angles in a fine angular grid with a highly modulated beam and then makes this plan deliverable within practical treatment time by an iterative fluence map merging and sequencing algorithm. We propose two changes to this method. First, we regularize the ideal plan obtained in the first step by adding an explicit constraint on treatment time. Second, we propose a different merging criterion that comprises of identifying and merging adjacent maps whose merging results in the least degradation of radiation dose. Results: The effect of both suggested modifications is evaluated individually and jointly on clinical prostate and paraspinal cases. Details of the two cases are reported. Conclusions: In the authors’ computational study they found that both proposed modifications, especially the regularization, yield noticeably improved treatment plans for the same treatment times than what can be obtained using the original VMERGE method. The resulting plans match the quality of 20-beam step-and-shoot IMRT plans with a delivery time of approximately 2 min.

60 APPLIED LIFE SCIENCES↗

Methodology for Exploring Water and Hydropower Operating Criteria That Simultaneously Improve Economic and Environmental Considerations

Despite the reliability and flexibility of hydropower, the operation of hydroelectric power plants may have significant impacts on the downstream river system, including its water stage, sediment transport, and water temperature, ultimately affecting the ecology. To address these challenges, there is a need to identify water scheduling patterns that improve both hydropower economics and the environment relative to current operations. This paper presents a new methodology to explore promising operational criteria/rules that can achieve such improvements. Typical environmental impact statements and relicensing processes generally perform detailed site-specific analyses of a few alternatives that focus on reservoir water release operating rules and their associated environmental impacts. In contrast, the methodology presented in this article uses a widely applicable approach that explores a much larger solution space. This large set of potential alternatives can be represented in a multidimensional space for which one axis represents the economic value and the other axis quantify individual environmental impacts (e.g., sediment transport and fish growth), and they are explored via two approaches: a Monte Carlo simulation that identifies “win–win” alternatives and a multi-objective optimization problem that identifies Pareto-optimal alternatives.

13 HYDRO ENERGY↗

WE-AB-209-07: Explicit and Convex Optimization of Plan Quality Metrics in Intensity-Modulated Radiation Therapy Treatment Planning

Purpose: To formulate objective functions of a multicriteria fluence map optimization model that correlate well with plan quality metrics, and to solve this multicriteria model by convex approximation. Methods: In this study, objectives of a multicriteria model are formulated to explicitly either minimize or maximize a dose-at-volume measure. Given the widespread agreement that dose-at-volume levels play important roles in plan quality assessment, these objectives correlate well with plan quality metrics. This is in contrast to the conventional objectives, which are to maximize clinical goal achievement by relating to deviations from given dose-at-volume thresholds: while balancing the new objectives means explicitly balancing dose-at-volume levels, balancing the conventional objectives effectively means balancing deviations. Constituted by the inherently non-convex dose-at-volume measure, the new objectives are approximated by the convex mean-tail-dose measure (CVaR measure), yielding a convex approximation of the multicriteria model. Results: Advantages of using the convex approximation are investigated through juxtaposition with the conventional objectives in a computational study of two patient cases. Clinical goals of each case respectively point out three ROI dose-at-volume measures to be considered for plan quality assessment. This is translated in the convex approximation into minimizing three mean-tail-dose measures. Evaluations of the three ROI dose-at-volume measures on Pareto optimal plans are used to represent plan quality of the Pareto sets. Besides providing increased accuracy in terms of feasibility of solutions, the convex approximation generates Pareto sets with overall improved plan quality. In one case, the Pareto set generated by the convex approximation entirely dominates that generated with the conventional objectives. Conclusion: The initial computational study indicates that the convex approximation outperforms the conventional objectives in aspects of accuracy and plan quality.

60 APPLIED LIFE SCIENCES↗

Multicriteria cost–benefit assessment of tannery production: The need for breakthrough process alternatives beyond conventional technology optimization

The worldwide use of chromium-based processes in tanneries generates increased concerns about their related environmental burdens. Cleaner production alternatives for leather production are being proposed, based on the optimization of specific aspects or criteria, for instance, reducing demand for specific materials and energy, or reducing local toxicological emissions. While improvement on individual characteristics of the process is certainly to be favored, a more comprehensive evaluation of alternatives is also needed to prevent the risk of shifting the burden to increase global load while addressing one specific critical factor of production. This work aims to discuss the importance of a multicriteria, multiscale approach to address cleaner production strategy costs and benefits. For this, materials balance, an economic approach, and emergy (with an “m”) accounting methods are applied to selected unhairing/liming, pickling/tanning and wastewater treatment steps in a tannery process, which was chosen as a case study. Results show that the assessed recycling cleaner production strategies assessed allow the manufacturer to reduce by one half the amount of water used and the demand for chemicals up to 4% with respect to the business-as-usual process, at the expense of increasing electricity demand by 10%. Economic cost-to-benefit ratio was 25$ benefits per 1$ invested, as well as an emergy-based cost-to-benefit of 33Em$ per 1Em$ invested, of course these improvements were limited to the three investigated process steps. The improvement in cost/benefit ratios indicates that converting scenario #0 into #1 is favorable under economic and emergy views. However, when the two scenarios are investigated from the point of view of the imbalance in local and renewable resource use versus imported and nonrenewable use, the emergy method shows a small overall increase in renewability (from 3.51% to 3.85%), a low, but expected, emergy yield ratio equal to 1, and a high environmental loading ratio (24.95 and 27.47). While the environmental cost–benefit ratio shows that recycling is a favorable option, the emergy performance indicators highlight that the efficiency of recycling is still insufficient and improvements in the tanning processes are needed to ensure renewability and sustainability. A number of process chemicals were involved in the investigated tannery operations, which required emergy evaluations. As a side result of this study, the Unit Emergy Values (UEVs) of SO{sub 2}, H{sub 2}SO{sub 4} Na{sub 2}SO{sub 4}, HCL, Na{sub 2}S, NaOH, CaO, Ca(OH){sub 2}, Cr{sub 2}O{sub 3}, MnSO{sub 4}, and Al(OH){sub 3}, were also calculated thus adding to the emergy database about chemicals. - Highlights: • Cleaner production strategies for tannery processes are presented and evaluated. • Local and global scales are considered under economical and biophysical approaches. • A multicriteria approach should be considered for decision making. • Recycling strategies have better indicators than traditional processes. • Emergy integrates energy and monetary indicators for more comprehensive assessment.

54 ENVIRONMENTAL SCIENCES↗

Multiobjective optimization techniques for structural design

The multiobjective programming techniques are important in the design of complex structural systems whose quality depends generally on a number of different and often conflicting objective functions which cannot be combined into a single design objective. The applicability of multiobjective optimization techniques is studied with reference to simple design problems. Specifically, the parameter optimization of a cantilever beam with a tip mass and a three-degree-of-freedom vabration isolation system and the trajectory optimization of a cantilever beam are considered. The solutions of these multicriteria design problems are attempted by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It has been observed that the game theory approach required the maximum computational effort, but it yielded better optimum solutions with proper balance of the various objective functions in all the cases.

Rao, S. S.↗