Incremental Evaluation Research Articles

Credulous acceptance in high-order argumentation frameworks with necessities: An incremental approach

Argumentation is an important research area in the field of AI. There is a substantial amount of work on different aspects of Dung's abstract Argumentation Framework (AF). Two relevant aspects considered separately so far are: i) extending the framework to account for recursive attacks and supports, and ii) considering dynamics, i.e., AFs evolving over time. In this paper, we jointly deal with these two aspects. We focus on High-Order Argumentation Frameworks with Necessities (HOAFNs) which allow for attack and support relations (interpreted as necessity) not only between arguments but also targeting attacks and supports at any level. We propose an approach for the incremental evaluation of the credulous acceptance problem in HOAFNs, by “incrementally” computing an extension (a set of accepted arguments, attacks and supports), if it exists, containing a given goal element in an updated HOAFN. In particular, we are interested in monitoring the credulous acceptance of a given argument, attack or support (goal) in an evolving HOAFN. Thus, our approach assumes to have a HOAFN Δ, a goal ϱ occurring in Δ, an extension E for Δ containing ϱ, and an update u establishing some changes in the original HOAFN, and uses the extension for first checking whether the update is relevant; for relevant updates, an extension of the updated HOAFN containing the goal is computed by translating the problem to the AF domain and leveraging on AF solvers. We provide formal results for our incremental approach and empirically show that it outperforms the evaluation from scratch of the credulous acceptance problem for an updated HOAFN.

An effective free-meshing and linear Step-Wise procedure to predict crack initiation and propagation

An automated procedure is proposed to calculate fracture initiation and propagation in two-dimensional structures. The application uses and enriches the Hybrid Semi-Analytical Method to calculate mixed-mode stress intensity factors in linear elastic fracture mechanics framework. The strategy does not necessitate prior knowledge of the starting crack tip location within the structure, resulting in suitable for analyzing structures without initial defects. When neither a priori invitation nor pre-existing notch is provided, the fracture initiation is assumed to occur when the structure reaches its elastic limit, and a non-linear analysis is conducted under the prescribed load to identify the first occurrence of permanent strain and to locate where the crack opening occurs. As the crack propagates, solely linear elastic analyses are performed to calculate the stress intensity factors. Relying upon these parameters, the procedure implements an evolutionary algorithm based on a step-by-step evaluation of the crack increment and direction. A global–local energy-based criterion is employed to drive fracture propagation. Neither local refinement nor mapped meshes around the crack tip are required, resulting in a streamlined and efficient free-meshing strategy.The calculation has been implemented in a standard finite element environment, and several numerical examples have been investigated, both from a qualitative and quantitative point of view. Qualitative crack paths have been shown for a square hollow plate under pure tensile and shear loads, and a modified Single Edge Notched specimen in bending, as a function of the mutual void positions, distance from the plate edges, and different notch lengths. Finally, an effective comparison in terms of forces-displacement curves has been presented between the proposed procedure, and a lab test for a modified Compact Tension specimen under tensile loading, demonstrating the overall accuracy and reliability of the presented strategy.It is felt that the proposed procedure could pave the way for designing hollowed structures and investigating the corresponding evolutionary laws that relate structural geometries to the insurgence and spread of fractures, and envisaging crack initiation and propagation within inhomogeneous media.

Heuristic Search for Rank Aggregation with Application to Label Ranking

Rank aggregation combines the preference rankings of multiple alternatives from different voters into a single consensus ranking, providing a useful model for a variety of practical applications but posing a computationally challenging problem. In this paper, we provide an effective hybrid evolutionary ranking algorithm to solve the rank aggregation problem with both complete and partial rankings. The algorithm features a semantic crossover based on concordant pairs and an enhanced late acceptance local search method reinforced by a relaxed acceptance and replacement strategy and a fast incremental evaluation mechanism. Experiments are conducted to assess the algorithm, indicating a highly competitive performance on both synthetic and real-world benchmark instances compared with state-of-the-art algorithms. To demonstrate its practical usefulness, the algorithm is applied to label ranking, a well-established machine learning task. We additionally analyze several key algorithmic components to gain insight into their operation. History: Accepted by Erwin Pesch, Area Editor for Heuristic Search & Approximation Algorithms. Funding: This work was supported by the National Natural Science Foundation of China [Grant 72371157] and Shanghai Pujiang Programme [Grant 23PJC069]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0019 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0019 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Implementing just climate adaptation policy: An analysis of recognition, framing, and advocacy coalitions in Boston, U.S.A.

Cities face intersectional challenges implementing climate adaptation policy. This research contributes to scholarship dedicated to understanding how policy implementation affects socially vulnerable groups, with the overarching goal of promoting justice and equity in climate policy implementation. We apply a novel framework that integrates social justice theory and the advocacy coalition framework to incrementally assess just climate adaptation in Boston, Massachusetts in the United States. Boston made an ambitious commitment to address equity as part of its climate planning and implementation efforts. In this paper, we evaluate the first implementation stage over the period 2016–2019 during which Boston developed coastal resilience plans for three neighborhoods. Despite Boston's commitment to equity, we find injustice was nevertheless reproduced through representation and coalition dynamics, the framing of problems and solutions, and a failure to recognize the priorities and lived experiences of city residents. The assessment framework presented can be adapted to evaluate how other climate adaptation initiatives advance social justice and highlights the need for incremental evaluation over short time periods to inform ongoing implementation efforts.

Self-Supervised Reinforcement Learning with dual-reward for knowledge-aware recommendation

To improve the recommendation accuracy and offer explanations for recommendations, Reinforcement Learning (RL) has been applied to path reasoning over knowledge graphs. However, in recommendation tasks, most existing RL methods learn the path-finding policy using only a short-term or single reward, leading to a local optimum and losing some potential paths. To address these issues, we propose a Self-Supervised Reinforcement Learning (SSRL) framework combined with dual-reward for knowledge-aware recommendation reasoning over knowledge graphs. Then, we improve Actor–Critic algorithm by using a dual-reward driven strategy, which combines short-term reward with long-term incremental evaluation. The improved algorithm helps the policy guide path reasoning in an overall situation. In addition, to find the most potential paths, in the improved Actor–Critic algorithm, a loss constraint of each sample is used as a reinforced signal to update the gradients. With some improvements against baselines, experimental results demonstrate the effectiveness of our framework.

Incremental Evaluation Model for the Analysis of Indoor Air Measurements

The investigation of the cleaning effectiveness of air cleaners under realistic conditions is challenging. Mathematical models are needed to extract characteristic properties of the air cleaning system from experimental data. An incremental evaluation model based on a source term and a total first-order loss coefficient in each segment was developed to analyze indoor particle measurements. The application of the model is demonstrated using two scenarios, one in a well-mixed testing room and another in a fully equipped aircraft cabin at 750 hPa with a typical aircraft ventilation system. In the first scenario, a normalized version of the model is used to eliminate the source’s influence. For the investigation in the aircraft cabin, the model served to extract temporal and spatial resolved source terms and first-order loss coefficients. The incremental evaluation model is applicable to enhance the certification of air cleaners. The application of the model is not only limited to particles; measurements of gaseous compounds like ozone, carbon dioxide, or volatile organic compounds can be evaluated analogously. The model’s utility for the data analysis of experiments with complex flow conditions should be studied in further investigations.

Economic Evaluation Method of Incremental Distribution Network Project Based on Value Theory

In order to improve the weight calculation accuracy and overall evaluation accuracy of incremental distribution network project economic evaluation, a new incremental distribution network project economic evaluation method based on value theory is proposed in this paper. Firstly, based on the value theory, the economic characteristics of incremental distribution network are analyzed. Secondly, the economic benefits of the incremental distribution network project are calculated from the perspectives of DG owned operators and DG owned users. Finally, based on the calculation results of economic benefits, this paper constructs the evaluation index system, calculates the evaluation weight from both subjective and objective aspects, and finally completes the economic evaluation of incremental distribution network project. The experimental results show that compared with the traditional evaluation methods, this method can accurately calculate the evaluation weight, so as to obtain more accurate evaluation results.

Incremental rough reduction with stable attribute group

In dynamic and open data environment, how to improve the performance of reduction is of great importance from incremental evaluation of attributes and quick search of attributes. In this paper, by considering both two perspectives, we first combine the incremental technology and the accelerated strategy in attribute reduction. On the one hand, we utilize the stable attribute group generated by DBSCAN to accelerate the process of searching reduction. On the other hand, we propose the matrix-based incremental mechanisms to dynamic attribute reduction when the objects are evolved over time. Moreover, these two methods are fused together in a unified algorithm of reduction. Finally, a series of comparative experiments is conducted to verify the effectiveness of proposed approach from stability, computational cost, and classification accuracy.

A sector-wide response to national policy on client-centred care and support: a document analysis of the development of a range of instruments to assess clients\u2019 experiences in the care and support for people with (intellectual) disabilities

BackgroundClient-centred care serves as the foundation for healthcare policy. Indeed, various instruments for assessing clients’ experiences of care and support are increasingly used to provide insights into the quality, and client-centred nature, of the care and support provided, which, in turn, aids the development of subsequent improvements. The unique characteristics of care and support for people with intellectual disabilities (ID), such as the need for both lifelong and life-wide care and support across all aspects of clients’ lives, led to an initiative within Dutch ID care to jointly develop a range of instruments to assess the experiences of clients receiving ID care and support. Individual clients’ experiences and suggestions for improvement, which are embedded in clients’ care plan cycles, constitute the foundation of this Range of Instruments. This paper provides a unique, bottom-up, exhaustive account of the process of developing the Range of instruments used to assess the experiences of clients in the field of Dutch ID care.MethodsRelevant documents at three levels (i.e. 1) national documents, such as policy papers and governmental reports, 2) documents and reports from the Dutch Association of Healthcare Providers for People with Disabilities (VGN) along with minutes from the meetings of the expert Committee who assessed the instruments, and 3) correspondence between the Committee and developers as well as the forms used in the assessment process for each instrument) were qualitatively analysed by two researchers who had no affiliation with the development of the Range of instruments used to assess clients’ experiences in ID care and support. All of the documents were inductively coded using a thematic analytical approach. Informants who were either currently or previously involved in the development of these instruments were asked to provide clarification over the documents themselves and to explain the context in which they were produced.ResultsThe development of the range of instruments can be classified into four phases, namely: 1) supporting the bottom-up development of initiatives to assess clients’ experiences, 2) focusing on learning and further development, 3) stimulating exchange between the developers and users of the instruments and the Committee responsible for assessing them, and 4) further development in response to the changing times and new landscape.ConclusionsThe range of instruments were found to be appropriate for a variety of clients in ID care and support, specifically in terms of assessing their individual experiences and gaining insight into their suggestions for improvement, and effective in terms of collaboratively improving the quality of ID care and support. In so doing, these instruments potentially provide an avenue through which clients’ experiences can be embedded in the process of ID care and support. Other specific features in the development of these instruments, namely their incremental adoption, ongoing evaluation and strong practice orientation, were also found to be suitable for other care contexts’ attempts to respond to the top-down policy objectives of client-centeredness and translating outcomes into direct care practice.

Accuracy of vertebral puncture in percutaneous vertebroplasty

PurposeTo clarify the accuracy of vertebral puncture of the vertebral tertile area needling (VETERAN) method puncturing the pedicle superimposed on one-third of the width between the lateral vertebral line to the contralateral medial lamina line compared with Cathelin-needle-assisted puncture (CAP) method puncturing using the Cathelin needle as a guide in percutaneous vertebroplasty.Materials and methods449 punctures by CAP method and 125 punctures by VETERAN method were enrolled. We compared the puncture accuracy of both methods. We estimated a vertebral estimated tilting ratio (VET-ratio) defined as ratio of the distance between the lateral vertebral line and the contralateral medial laminal line to the distance between the vertebral lateral line and the puncture point measured by computed tomography. We also estimated the procedural items and clinical outcomes.ResultsVETERAN method with 100% of punctures within safe zone (cortical breaches within 2 mm) had significantly higher accuracy than CAP method with 97.8% (p < 0.01) for the 2 mm incremental evaluation. No cases with a VET-ratio of 36% or less had cortical breaches. VETERAN method had shorter operative time per puncture (p < 0.01) and exposure time per puncture (p < 0.05).ConclusionVETERAN method reduced the occurrence of the inaccurate puncture, operative times, and exposure times. A VET-ratio with 36% or less is associated with a safe puncture using VETERAN method.

JavaDL: automatically incrementalizing Java bug pattern detection

Static checker frameworks support software developers by automatically discovering bugs that fit general-purpose bug patterns. These frameworks ship with hundreds of detectors for such patterns and allow developers to add custom detectors for their own projects. However, existing frameworks generally encode detectors in imperative specifications, with extensive details of not only what to detect but also how . These details complicate detector maintenance and evolution, and also interfere with the framework’s ability to change how detection is done, for instance, to make the detectors incremental. In this paper, we present JavaDL, a Datalog-based declarative specification language for bug pattern detection in Java code. JavaDL seamlessly supports both exhaustive and incremental evaluation from the same detector specification. This specification allows developers to describe local detector components via syntactic pattern matching , and nonlocal (e.g., interprocedural) reasoning via Datalog-style logical rules . We compare our approach against the well-established SpotBugs and Error Prone tools by re-implementing several of their detectors in JavaDL. We find that our implementations are substantially smaller and similarly effective at detecting bugs on the Defects4J benchmark suite, and run with competitive runtime performance. In our experiments, neither incremental nor exhaustive analysis can consistently outperform the other, which highlights the value of our ability to transparently switch execution modes. We argue that our approach showcases the potential of clear-box static checker frameworks that constrain the bug detector specification language to enable the framework to adapt and enhance the detectors.

Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization

Chemical diversity is one of the key term when dealing with machine learning and molecular generation. This is particularly true for quantum chemical datasets. The composition of which should be done meticulously since the calculation is highly time demanding. Previously we have seen that the most known quantum chemical dataset QM9 lacks chemical diversity. As a consequence, ML models trained on QM9 showed generalizability shortcomings. In this paper we would like to present (i) a fast and generic method to evaluate chemical diversity, (ii) a new quantum chemical dataset of 435k molecules, OD9, that includes QM9 and new molecules generated with a diversity objective, (iii) an analysis of the diversity impact on unconstrained and goal-directed molecular generation on the example of QED optimization. Our innovative approach makes it possible to individually estimate the impact of a solution to the diversity of a set, allowing for effective incremental evaluation. In the first application, we will see how the diversity constraint allows us to generate more than a million of molecules that would efficiently complete the reference datasets. The compounds were calculated with DFT thanks to a collaborative effort through the QuChemPedIA@home BOINC project. With regard to goal-directed molecular generation, getting a high QED score is not complicated, but adding a little diversity can cut the number of calls to the evaluation function by a factor of ten

Optimizing Thermal Efficiencies of Double-Pass Cross-Corrugated Solar Air Heaters on Various Configurations with External Recycling

The effect of external-recycle operations on the thermal performance of double-pass cross-corrugated solar air heaters (SAH) under different operating conditions was investigated experimentally and theoretically. Additionally, the simultaneous ordinary equations were solved analytically for each proposed configuration. Four recycling types are introduced for improving the solar thermal performance with different external recycle processes, which are expected to enhance the heat transfer coefficient with a convective turbulent flow between the air and the absorber in the present study. Using recycling double-pass operations, two processes were conducted sequentially: air first flowed over the sinusoidal corrugated absorber plate and then flowed back later over the transverse sinusoidal corrugated bottom plate. Improved device performance was achieved due to the doubled heat transfer area over and under the corrugated absorber plate, from which both the sinusoidal cross-corrugated absorber plate and bottom plate enhanced turbulent intensity. Theoretical predictions and experimental results both indicated that the recycle ratio increased with the SAH thermal efficiency for all proposed designs. The results show a higher heat transfer efficiency for the proposed four configurations using wavelike corrugated plates compared to those conducted in single-pass and flat-plate absorber plates with up to a maximum 133% (from 0.301 to 0.703) increment. The optimal device performance was examined for all external-recycle configurations under the same working dimensions and operational conditions. The best configuration for optimal thermal performance was the device that lengthened the air flow pathway and increased the air velocity within the collector; thus, a higher heat transfer rate was accomplished. The evaluation of increments in the power consumption and of the heat-transfer efficiency enhancement together determined the optimal design based on an economic consideration across various configurations of cross-corrugated double-pass devices.

HyMAC

Distributed matrix computation is common in large-scale data processing and machine learning applications. Iterative-convergent algorithms involving matrix computation share a common property: parameters converge non-uniformly. This property can be exploited to avoid redundant computation via incremental evaluation . Unfortunately, existing systems that support distributed matrix computation, like SystemML, do not employ incremental evaluation. Moreover, incremental evaluation does not always outperform classical matrix computation, which we refer to as a full evaluation . To leverage the benefit of increments, we propose a new system called HyMAC , which performs hybrid plans to balance the trade-off between full and incremental evaluation at each iteration. In this demonstration, attendees will have an opportunity to experience the effect that full, incremental, and hybrid plans have on iterative algorithms.

Detection of subsurface bruising in fresh pickling cucumbers using structured-illumination reflectance imaging

Pickling cucumbers are susceptible to bruising during harvest and postharvest handling. It is thus desirable to segregate bruised fruit before they are marketed as fresh products or processed as pickles. Structured-illumination reflectance imaging (SIRI) is an emerging optical imaging modality for food quality inspection. This study reported the first demonstration of SIRI for detecting subsurface bruising in fresh pickling cucumbers. Two independent sets of images, i.e., direct component (DC) and amplitude component (AC), were demodulated from phase-shifted sinusoidal pattern images at 740 nm; AC was found more effective than DC for ascertaining bruises that exhibited no visual symptoms. Classification models based on support vector machine were built using extracted image features, to classify cucumbers into bruised and normal classes. The highest classification accuracy of 91 % was achieved by the ensemble of DC, AC and their ratio (AC/DC) images, which represented 7.6 percentage-point improvement over that obtained using the DC images alone. Using features selection for five sets of image features led to further improvements in the classification performance. Incremental evaluation of top 50 most informative features resulted in an averaged overall accuracy of 94 %, with the highest accuracy of 97 % attained by 31 features; and using a subset of only 5 features, 3 from AC and 2 from DC, also produced a high overall accuracy of 96 %. This study demonstrates that SIRI can provide a potentially effective means for visualizing subsurface bruising in pickling cucumbers, which otherwise could barely be achieved by imaging under uniform illumination, and thus for enhancing the differentiation of normal and bruised fruit. More research is, however, needed to optimize and implement SIRI for real-time inspection of cucumber defects.

Weighting-based Variable Neighborhood Search for Optimal Camera Placement

The optimal camera placement problem (OCP) aims to accomplish surveillance tasks with the minimum number of cameras, which is one of the topics in the GECCO 2020 Competition and can be modeled as the unicost set covering problem (USCP). This paper presents a weighting-based variable neighborhood search (WVNS) algorithm for solving OCP. First, it simplifies the problem instances with four reduction rules based on dominance and independence. Then, WVNS converts the simplified OCP into a series of decision unicost set covering subproblems and tackles them with a fast local search procedure featured by a swap-based neighborhood structure. WVNS employs an efficient incremental evaluation technique and further boosts the neighborhood evaluation by exploiting the dominance and independence features among neighborhood moves. Computational experiments on the 69 benchmark instances introduced in the GECCO 2020 Competition on OCP and USCP show that WVNS is extremely competitive comparing to the state-of-the-art methods. It outperforms or matches several best performing competitors on all instances in both the OCP and USCP tracks of the competition, and its advantage on 15 large-scale instances are over 10%. In addition, WVNS improves the previous best known results for 12 classical benchmark instances in the literature.

Query Rewriting for Incremental Continuous Query Evaluation in HIFUN

HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, where queries are evaluated. In this paper, we present a methodology based on the HIFUN language, and the corresponding algorithms for the incremental evaluation of continuous queries. In essence, our approach is able to process the most recent data batch by exploiting already computed information, without requiring the evaluation of the query over the complete dataset. We present the generic algorithm which we translated to both SQL and MapReduce using SPARK; it implements various query rewriting methods. We demonstrate the effectiveness of our approach in temrs of query answering efficiency. Finally, we show that by exploiting the formal query rewriting methods of HIFUN, we can further reduce the computational cost, adding another layer of query optimization to our implementation.

Dendrochronological study of Cedrus deodar Grown at Kumrat valley Dir Upper KPK, Pakistan: Evaluation of Tree Age and Increment Based on Increment Core

The present research was conducted for tree-rings study in a mixed stand of Himalayan Species Credur deodar in Kumrat valley Dir Upper KPK, Pakistan. Tree-rings analysis was related to the counting of tree ring. Random sampling method was used, and 70 sample trees were selected, tree heights and diameters were measured, and increment cores were collected from each sample-tree diameter at the height at breast point to be analyzed and studied in the laboratory. The objectives of the study were to determine the exact age of tree and to evaluate total and mean annual increment in the basal area and tree volume based on the increment cores. Regression models revealed the impacts of tree age on the basal area and tree-volume increment. Results showed the minimum basal-area increment was 0.0028 m2 at the age of 10 years, the maximum basal-area increment was 2.658 m2 at the age of 60 years, with mean was 0.95±0.677 m2 at the age of 36 years and R2 was 0.9593. The maximum tree-volume increment was 1.42 m3 at the age of 60 years, the minimum tree-volume increment was 0.010 m3 at the age of 10 years, with mean was 1.35±0.96 m3 at the age of 36 years and R2 was 0.9167. The minimum mean annual-basal area increment was 0.0027 m2, the maximum mean annual-basal area increment was 0.048 m2, and the average increment was 0.022±0.010 m2. The maximum mean-annual increment in tree volume was 0.068 m3 at the age of 60 years, the minimum mean-annual increment was 0.0039 m3 at the age of 10 years, with mean was 0.032±0.014 m3 at the age of 36 years and R2 was 0.8903. Results showed a strong positive relationship of tree age with area and volume increment.&#x0D; Keywords: Basal area, increment, tree age, volume

Ultimate strength assessment of stiffened panel under uni-axial compression with non-linear equivalent single layer approach

Steel stiffened panels are widely used in engineering design and construction. However, numerical modeling and analysis effort for a three-dimensional (3D) stiffened panel may be notable, especially for the ultimate limit state of ship structures. Therefore, a homogenization method is outlined that transforms 3D stiffened panel into an Equivalent Single Layer (ESL) concerning the same mechanical behavior. ESL stiffnesses are obtained with a unit cell analyses based on stiffened panel where periodicity is imposed with boundary conditions based on a first-order shear deformation theory (FSDT). Stiffnesses were determined from the first derivative of a membrane force and bending moment obtained with numerical simulations. The effect of initial imperfection shape was included in the analysis to account for local and global buckling behavior. ESL with non-linear stiffness was implemented in Abaqus UGENS subroutine, allowing incremental evaluation of stiffness. Ultimate strength prediction of a steel grillage model with ESL finite element analysis was in excellent agreement with detailed 3D FEM analysis. The key in this analysis was consideration of non-linear ESL stiffness as linear analysis was unable to detect the point where ultimate strength capacity of the grillage was reached.

A dynamic programming-based local search algorithm for solving the dynamic bipartite drawing problem

The dynamic bipartite drawing problem is a challenging NP-hard combinatorial optimization problem with numerous applications. In this study, we propose a dynamic programming-based local search (DP-LS) algorithm for solving it. Unlike previous metaheuristics reported in the literature, which move just one vertex (or two vertices) at each neighborhood iteration, the proposed DP-LS algorithm selects and performs multiple independent neighborhood moves at the same time to enhance the search efficiency. Generally, starting from a random initial solution, DP-LS iteratively explores the search space by integrating the DP-LS to locate local optima, and then uses a perturbation procedure to escape from the local optima. In addition, the proposed incremental evaluation techniques of the insert and swap moves enhance the efficiency of the neighborhood evaluation. Extensive computational experiments on two sets of 1120 problem instances indicate that the proposed DP-LS is highly competitive with the best-performing algorithms (including the general purpose solver Gurobi) in terms of both solution quality and computational efficiency. We analyzed the dynamic programming mechanism in the proposed DP-LS algorithm to determine its effectiveness (increasing the search efficiency tens of times). Not only can the proposed DP-LS algorithm be used to solve the DBDP, it can also be used as a general methodology for solving other combinatorial optimization problems, especially permutation optimization problems.