Four-layer framework for combinatorial optimization problems domain

Four-layer framework for combinatorial optimization problems/models domain is suggested for applied problems structuring and solving: (1) basic combinatorial models and multicriteria decision making problems (e.g., clustering, knapsack problem, multiple choice problem, multicriteria ranking, assignment/allocation); (2) composite models/procedures (e.g., multicriteria combinatorial problems, morphological clique problem); (3) basic (standard) solving frameworks, e.g.: (i) Hierarchical Morphological Multicriteria Design (HMMD) (ranking, combinatorial synthesis based on morphological clique problem), (ii) multi-stage design (two-level HMMD), (iii) special multi-stage composite framework (clustering, assignment/location, multiple choice problem); and (4) domain-oriented solving frameworks, e.g.: (a) design of modular software, (b) design of test inputs for multi-function system testing, (c) combinatorial planning of medical treatment, (d) design and improvement of communication network topology, (e) multi-stage framework for information retrieval, (f) combinatorial evolution and forecasting of software, devices. The multi-layer approach covers ‘decision cycle’, i.e., problem statement, models, algorithms/procedures, solving schemes, decisions, decision analysis and improvement.     

Structural composition of the telemetry system

Consideration was given to the combinatorial hierarchical design (composition) of the structure of an application telemetry system consisting of the on-board, radio, and ground communication equipment including the operator working place. The principal use was of the three-stage hierarchical morphological multicriterial design: (a) design of the tree model of the system in the form of the AND-OR tree and generation of the design alternatives for the hanging vertices of the constructed model (system parts/components), (b) multicriterial selection of the design alternatives for the parts of the designed system, (c) generation of the resulting combination of the selected alternatives taking into consideration their ordinal quality and compatibility. The process of hierarchical modular design is illustrated by the example of an application.     

System synthesis with morphological clique problem: fusion of subsystem evaluation decisions

The article focuses on the analysis and evaluation of composite systems on the basis of ordinal estimates for system components. This viewpoint corresponds to system synthesis as an integration (fusion) of local decisions into a global one. We examine hierarchical (tree-like) models for composite systems and consider the following: (1) traditional multi-criteria evaluation approaches; (2) morphological clique problem with special discrete spaces for evaluation of system excellence; and (3) generalization of morphological clique problem. The generalization of morphological clique problem is based on the following: (a) structure of compatibility between system components and its influence to problem complexity, (b) some kinds of compatibility for the components (e.g., asymmetric, negative), and (c) poset-like scales for system components (local decisions) and their aggregation into a scale for a resultant global decision. We consider four basic versions of poset-like scales for system components and several corresponding extended modified discrete spaces of system excellence. Numerical examples illustrate the material (e.g., scales, aggregation of scales, algorithms).     

Combinatorial optimization in system configuration design

The significance of systems configurations has been increased in many applied domains (e.g., software, hardware, manufacturing systems, communication systems, supply chain systems, solving strategies, modular planning, material engineering and combinatorial chemistry). Generally, the following kinds of systems under configuration (reconfiguration) can be examined: (a) initial data/infomation (or row materials); (b) processing systems (machines, computers, algorithms); (c) resultant decisions (e.g., products, plans); (d) applied support systems (e.g., network systems, services); (e) requirements; and (f) standards. In the paper several system configuration problems are investigated: (i) searching for (selection of) a set (structure) of system components, (ii) searching for a set of compatible system components, (iii) allocation of system components, (iv) reconfiguration of a system as redesign of the system structure, (v) multi-stage design and redesign of system configuration, (vi) design or redesign of the system configuration for multi-product systems, and (vii) design of system hierarchy. Combinatorial optimization models (including multicriteria statements) are under examination: multiple choice problem, allocation problem, graph coloring problems, morphological clique problem (with compatibility of system components), multipartite clique and their modifications, spanning trees problems.     

Combinatorial scheme for management of life cycle: Example for concrete macrotechnology

The paper describes a combinatorial scheme for the analysis and synthesis of product life cycle on the basis of a typical compressed structure: design of materials and manufacturing process. In addition, the following problems are studied: system refinement, series-parallel production process, and multistage design (design of product trajectories). Hierarchical combinatorial morphological approach is proposed. The solving process is based on ordinal expert knowledge. The following phases are examined: design of a basic system morphology, generation of local design alternatives, knowledge acquisition as ordinal estimates for local design alternatives and their compatibility, and synthesis of the best compositions.A realistic numerical example for concrete-macrotechnology (composing of concrete from constituents and selection of manufacturing alternatives) illustrates the approach.     

A Multicriteria Collaborative Filtering Approach Using the Indifference Relation and its Application to Initiator Recommendation for Group-Buying

For recommender systems, the main aim of the popular collaborative filtering approaches is to recommend items that users with similar preferences have liked in the past. Single-criterion recommender systems have been successfully used in several applications. Because leveraging multicriteria information can potentially improve recommendation accuracy, multicriteria rating systems that allow users to assign ratings to various content attributes of items they have consumed have become the focus in recommendation systems. By treating the recommendation of items as a multicriteria decision problem, it is interesting to incorporate the preference relation of users of multicriteria decision making (MCDM) into the similarity measure for a collaborative filtering approach. For this, the well-known indifference relation can justify a discrimination or similarity between any two users, if outranking relation theory is incorporated. The applicability of the proposed single-criterion and multicriteria recommendation approaches to the recommendation of initiators on a group-buying website was examined. Experimental results have demonstrated that the generalization ability of the proposed multicriteria recommendation approach performs well in comparison to other single-criterion and multicriteria collaborative filtering approaches.     

An approach to solving discrete vector optimization problems over a combinatorial set of permutations

Complex discrete multicriteria problems over a combinatorial set of permutations are analyzed. Some properties of an admissible domain for a combinatorial multicriteria problem embedded into an arithmetic Euclidian space are considered. Optimality conditions are obtained for different types of effective solutions. A new approach to solving the problems formulated is constructed and substantiated. This work was supported by the Fundamental Research Fund of Ukraine (project Φ251/094). __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 158–172, May–June 2008.     

淮委综合应用门户整合的设计与实现

为顺应国家对于“互联网 + 政务服务”建设要求，解决现有业务应用孤立和信息分散的问题，淮河水利委员会开展综合应用门户整合建设，采用分层开放的体系架构，以“汇聚、提醒、定制”为三大设计理念， 基于主流成熟的技术，对数据资源、应用服务和业务系统等进行有效整合，形成一站式的综合性应用门户，提供待办事项前置提醒、业务信息汇聚展示和应用单点登录等便捷化服务。目前门户系统已正式运行，显著提高日常办公效率，加强应用安全的防护能力，同时具有很好的兼容性、稳定性和扩展性，可适用于水利行业及类似门户的整合建设。     

A Multicriteria Method for Identification and Forecasting

A multicriteria approach to identify and forecast mathematical models is considered. The need for such an approach arises, in particular, when it is necessary to take into account errors that cannot be reduced to one function and in the absence of specific information about the data interference class. The paper deals with a multicriteria version of the identification sets method based on approximating and visualizing the graph of the vector function of identification errors and its projections onto the space of identification parameters. The nearness function is introduced that describes the proximity of a criterion point to the set of nonimprovable (Pareto efficient) solutions of the identification problem. The efficient criteria set (Pareto frontier), the sets of efficient and subefficient parameters, and the corresponding forecast trajectory tubes are studied. To construct these objects, methods for approximating implicitly specified sets are used, in particular, methods for approximating the Edgeworth–Pareto hull and the deep holes method. The technique and examples for two criteria of identification quality are considered in detail.     

Capability-Aware Information Aggregation in Peer-to-Peer Grids

Information aggregation is the process of summarizing information across the nodes of a distributed system. We present a hierarchical information aggregation system tailored for Peer-to-Peer Grids which typically exhibit a high degree of volatility and heterogeneity of resources. Aggregation is performed in a scalable yet efficient way by merging data along the edges of a logical self-healing tree with each inner node providing a summary view of the information delivered by the nodes of the corresponding subtree. We describe different tree management methods suitable for high-efficiency and high-scalability scenarios that take host capability and stability diversity into account to attenuate the impact of slow and/or unstable hosts. We propose an architecture covering all three phases of the aggregation process: Data gathering through a highly extensible sensing framework, data aggregation using reusable, fully isolated reduction networks, and application-sensitive data delivery using a broad range of propagation strategies. Our solution combines the advantages of approaches based on Distributed Hash Tables (DHTs) (i.e., load balancing and self-maintenance) and hierarchical approaches (i.e., respecting administrative boundaries and resource limitations). Our approach is integrated into our Peer-to-Peer Grid platform Cohesion. We substantiate its effectiveness through performance measurements and demonstrate its applicability through a graphical monitoring solution leveraging our aggregation system.     

Multicriteria methods and logic aggregation in suitability maps

In this paper, we identify and describe fundamental logic properties of multicriteria methods for land‐use suitability analysis and the design of suitability maps. The existing multicriteria methods can be evaluated from the standpoint of their ability to support the necessary logic properties that affect the expressive power of evaluation methods. The paper investigates and compares simple additive scoring, multiattribute value technique, multiattribute utility technique, analytic hierarchy process, ordered weighted average, outranking methods, and logic scoring of preference (LSP). We introduce canonical forms of logic aggregation in suitability maps and show how to use canonical aggregation structures to design LSP suitability maps that evaluate distributions of points of interests (POIs) in urban areas. © 2011 Wiley Periodicals, Inc.     

A multi-agent approach to Intelligent Transportation Systems modeling with combinatorial auctions

Challenges of urbanization require new, more flexible approaches to design of public transportation systems. Demand Responsive Transport systems (DRT) that provide a share transportation services with flexible routes and focus on optimizing of economic and environmental value are becoming an important part of public transportation. In this paper we propose a new approach to design of DRT models which considers DRT as a multi-agent system (MAS) where various autonomous agents represent interests of system’s stakeholders. The distributed nature of the MAS facilitates design of scalable implementations in modern cloud environments. We also propose a planning algorithm based on combinatorial auctions (CA) that allows to express commodity of multiple transportation scenarios by evident means of the bids. Using the mechanism of CA we may fully take into account the presence of complementariness and substitutability among the items that differ across bidders. Further, we describe design principles of our proposed software with a prototype implementation. We believe that our approach to multi-agent modeling is general enough to provide the flexibility necessary for adoption of DRT-services modeling into real-world scenarios. The results of modeling have been compared against several cases of a local bus provider and validated in a set of computational experiments.     

Optimal design of underwater stiffened shells

The optimal design parameters of stiffened shells are determined using a rational multicriteria optimization approach. The adopted approach aims at simultaneously minimizing the shell vibration, associated sound radiation, weight of the stiffening rings as well as the cost of the stiffened shell. A finite element model is developed to determine the vibration and noise radiation from cylindrical shells into the surrounding fluid domain. The production cost as well as the life cycle and maintenance costs of the stiffened shells are computed using the Parametric Review of Information for Costing and Evaluation (PRICE) model. A Pareto/min-max multicriteria optimization approach is then utilized to select the optimal dimensions and spacing of the stiffeners. Numerical examples are presented to compare the vibration and noise radiation characteristics of optimally designed stiffened shells with the corresponding characteristics of plain un-stiffened shells. The obtained results emphasis the importance of the adopted multicriteria optimization approach in the design of quiet, low weight and low cost underwater shells which are suitable for various critical applications. Received September 14, 2000 Communicated by J. Sobieski     

Pythagorean fuzzy Bonferroni mean aggregation operator and its accelerative calculating algorithm with the multithreading

In this paper, we study the well‐known Bonferroni mean and develop its generalized aggregation operators in the Pythagorean fuzzy environment. More specifically, by considering the interrelationship between arguments with Pythagorean fuzzy information, we develop the Pythagorean fuzzy Bonferroni mean (PFBM) and some special properties and cases of them are also discussed. Furthermore, taking the multicriteria decision making environment into consideration, we extend the results of PFBM and develop the weighted Pythagorean fuzzy Bonferroni mean (WPFBM). Meanwhile, we also propose an approach for the application of WPFBM. However, during the application of the WPFBM operator, the calculation is very complex and time consuming. Hence, we introduce the multithreading into the application of the WPFBM operator and develop an accelerative calculating algorithm for it. To validate the performance of the accelerative calculating algorithm, we further design the corresponding experimental analysis.     

Fuzzy multiple attributes and multiple hierarchical decision making

A procedure is proposed to solve the multiple attributes and multiple hierarchical system under fuzzy environment. The approach is based on:

1. (1) fuzzy representation;

2. (2) hierarchical performance evaluation structure,

3. (3) gradient eigenvector method for rating the fuzzy criteria weighting, and

4. (4) using the max-min paired elimination method for aggregation.

To illustrate the approach, an example on the evaluation of teaching performance in higher education is solved.     

A multicriteria approach to two-level hierarchy scheduling in grids

In this paper we address a multicriteria scheduling problem for computational Grid systems. We focus on the two-level hierarchical Grid scheduling problem, in which at the first level (the Grid level) a Grid broker makes scheduling decisions and allocates jobs to Grid nodes. Jobs are then sent to the Grid nodes, where local schedulers generate local schedules for each node accordingly. A general approach is presented taking into account preferences of all the stakeholders of Grid scheduling (end-users, Grid administrators, and local resource providers) and assuming a lack of knowledge about job time characteristics. A single-stakeholder, single-criterion version of the approach has been compared experimentally with the existing approaches.     

A shell of an onboard online advisory expert system for typical flight situation “Introduction of a group into an air fight”

The following knowledge base is presented: a hierarchical two-level knowledge base of onboard online advisory expert system for the subject area “Introduction of a group into an air fight”, in which mechanisms of inference mechanisms by precedent and multicriteria choice are used along with production rules. Examples of partial filling the knowledge base for the general problem “Patrol Escort of Strike Air Forces” are given.     

Modularized design-oriented systematic inventive thinking approach supporting collaborative service innovations

The rapid evolution of new service systems raises crucial challenges for service design and requires effective methods. This study depicts a conceptual service design framework, called design-oriented systematic inventive thinking (DSIT) approach, which can be applied in different problem contexts. DSIT is presented as a new systematic and collaborative intelligence approach for creating and evaluating complex service systems using multi-criteria data analytics. DSIT synthesizes the current field of TRIZ service-design knowledge system and the emerging area of non-TRIZ service-design knowledge system. DSIT enables integrated development of service offerings at four dimensions and provides the matching integrated service design approach for each dimension. Four types of service design approaches are conceptualized as “human-independent service engineering,” “problem-clarified service engineering,” “solution-converged service engineering,” and “designing for service.” A new service computer-aided design system (service CAD) named DSIT explorer is developed consisting of customization, compatibility, and extensiveness of DSIT modules. A pervasive and smart collaborative service system (i.e., the smart MOS burger service solution) designed using DSIT explorer is illustrated. DSIT is a holistic, interdisciplinary, and collaborative service design concept, which is incorporated into a collaborative and intelligent service CAD framework to enable systematic inventive thinking throughout phases of service design lifecycle from problem definition, problem resolution, to solution evaluation.