A probabilistic cooperative–competitive hierarchical model for global optimization

Leung, Kwong‐Sak; King, Irwin; Wong, Yiu-Chung

doi:10.1016/j.amc.2005.08.045

Cited by 5 publications

(3 citation statements)

References 21 publications

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“…These relationships are very complex and flexible in practice. They can be simply classified into two categories, the cooperative and competitive relations [7,8]. In this study, the coordination models are classified into these two types.…”

Section: B Coordination Modelsmentioning

confidence: 99%

Study on Coordination Models of Container Logistics System

Liu¹

2009

2009 International Conference on Information Management, Innovation Management and Industrial Engineering

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Container logistics system is a concrete logistics system with the specialty that containerization simplifies and unifies the circulation process while it enlarges the system scale and makes it more complex. Coordination is becoming an effective mechanism to reduce the cost and improve the profit of container logistics system. From three aspects, the coordinated entities, the interaction models and the coordination content, the coordination model is studied. Then, the designing principles of coordination mechanisms are also studied. The paper studies the related concepts of container logistics system and the coordination mechanisms, which are beneficial to design the higher efficient system of container logistics.

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Section: B Coordination Modelsmentioning

confidence: 99%

Study on Coordination Models of Container Logistics System

Liu¹

2009

2009 International Conference on Information Management, Innovation Management and Industrial Engineering

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“…The inspiration for this issue is in the zone of stochastic booking where a progression of occupations ought to be booked on a machine within a confined amount of time. Thus, the trait of unchangeable choices is fundamental to the idea of our stochastic model [30].…”

Section: Stochastic Optimization and Adaptivitymentioning

confidence: 99%

Considering Stochastic and Combinatorial Optimization

Arasteh

2016

IJOR

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Here, issues connected with characteristic stochastic practices are considered. In the first part, the plausibility of covering the arrangements of an improvement issue on subjective subgraphs is studied. The impulse for this strategy is a state where an advancement issue must be settled as often as possible for discretionary illustrations. Then, a preprocessing stage is considered that would quicken ensuing inquiries by discovering a settled scattered subgraph covering the answer for an arbitrary subgraph with a high likelihood. This outcome is grown to the basic instance of matroids, in addition to advancement issues taking into account the briefest way and resource covering sets. Next, a stochastic improvement model is considered where an answer is sequentially finished by picking an accumulation of "points". Our crucial idea is the profit of adaptivity, which is investigated for an extraordinary sort of an issue. For the stochastic knapsack issue, the industrious upper and lower cutoff points of the "adaptivity hole" between ideal adaptive and non-adaptive methodologies are checked. Also, an algorithm is described that accomplishes a close ideal estimate. Finally, complicational results are shown to verify the optimal adaptive approaches.

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“…Newly, a general model for hierarchical optimization has been presented [23] based on the fact that global searching methods solve in general optimization problems by navigating on the surface of a possibly rugged landscape, which is the optimization function. This kind of navigation is not very effective because the property of the landscape at different resolutions can be very different.…”

Section: Hierarchical Optimization and Principal Componentsmentioning

confidence: 99%

Building Retrofitting using Hierarchical Optimization and Principal Component Analysis

Kanarachos¹,

Kanarachos²

2014

AJS

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In view of the needs for optimization (performance, costs) of building retrofitting, several methods have been proposed in the past. These methods are mostly based on multivariate analysis of data and on mathematical optimization methods. However, the complexity of the task reveals the need for further methodological developments. In this paper a new method based on Hierarchical Optimization (HO) and principal component analysis is proposed. Hierarchical optimization is concerned with decision making problems that involve multiple decision makers ordered within a hierarchical structure and has proved already its usefulness. It helps transforming a global optimization problem into a number of local ones, which also consort with engineering knowledge and practice. In this sense a principal component analysis helps greatly the definition of efficient sub-optimization problems. The above methodology is presented in the following and a case study illustrates its usefulness.

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A probabilistic cooperative–competitive hierarchical model for global optimization

Cited by 5 publications

References 21 publications

Study on Coordination Models of Container Logistics System

Study on Coordination Models of Container Logistics System

Considering Stochastic and Combinatorial Optimization

Building Retrofitting using Hierarchical Optimization and Principal Component Analysis

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