Computation of the Usage Contexts Coverage of a Jigsaw With CSP Techniques

2010 ◽  
Author(s):  
Bernard Yannou ◽  
Jiliang Wang ◽  
Pierre-Alain Yvars
Keyword(s):  
Constraint Satisfaction ◽  
Performance Prediction ◽  
Constraint Satisfaction Problem ◽  
Design Parameters ◽  
A Value ◽  
Product Service ◽  
Value Sets ◽  
Usage Context ◽  
A Performance

In the context of the Usage Context Based Design (UCBD) of a product-service, a taxonomy of variables is suggested to setup the link between the design parameters of a product-service and the part of a set of expected usages that may be covered. This paper implements a physics-based model to provide a performance prediction for each usage context that also depends on the user skill. The physics describing the behavior and consequently the performances of a jigsaw are established. Simulating numerically the usage coverage is non trivial for two reasons: the presence of circular references in physical relations and the need to efficiently propagate value sets or domains instead of accurate values. For these two reasons, we modeled the usage coverage issue as a Constraint Satisfaction Problem and we result in the expected service performances and a value of a covered usage indicator.

The Goldilocks problem

2003 ◽  
Vol 17 (1) ◽  
pp. 3-11 ◽  
Author(s):  
TUDOR HULUBEI ◽  
EUGENE C. FREUDER ◽  
RICHARD J. WALLACE
Keyword(s):  
Constraint Satisfaction ◽  
Feasible Solution ◽  
Constraint Satisfaction Problem ◽  
Real Life ◽  
Constraint Satisfaction Problems ◽  
Major Focus ◽  
Huge Number ◽  
Arc Consistency ◽  
A Value ◽  
Practical Standpoint

Constraint-based reasoning is often used to represent and find solutions to configuration problems. In the field of constraint satisfaction, the major focus has been on finding solutions to difficult problems. However, many real-life configuration problems, although not extremely complicated, have a huge number of solutions, few of which are acceptable from a practical standpoint. In this paper we present a value ordering heuristic for constraint solving that attempts to guide search toward solutions that are acceptable. More specifically, by considering weights that are assigned to values and sets of values, the heuristic can guide search toward solutions for which the total weight is within an acceptable interval. Experiments with random constraint satisfaction problems demonstrate that, when a problem has numerous solutions, the heuristic makes search extremely efficient even when there are relatively few solutions that fall within the interval of acceptable weights. In these cases, an algorithm that is very effective for finding a feasible solution to a given constraint satisfaction problem (the “maintained arc consistency” algorithm or MAC) does not find a solution in the same weight interval within a reasonable time when it is run without the heuristic.

scholarly journals A Hybrid Knowledge-Based Recommender for Product-Service Systems Mass Customization

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 296
Author(s):  
Laila Esheiba ◽  
Amal Elgammal ◽  
Iman M. A. Helal ◽  
Mohamed E. El-Sharkawi
Keyword(s):  
Recommender System ◽  
Mass Customization ◽  
Constraint Satisfaction Problem ◽  
Service Systems ◽  
Prototype System ◽  
Knowledge Based ◽  
Product Service ◽  
Wide Range ◽  
Hybrid Knowledge ◽  
Product Service Systems

Manufacturers today compete to offer not only products, but products accompanied by services, which are referred to as product-service systems (PSSs). PSS mass customization is defined as the production of products and services to meet the needs of individual customers with near-mass-production efficiency. In the context of the PSS mass customization environment, customers are overwhelmed by a plethora of previously customized PSS variants. As a result, finding a PSS variant that is precisely aligned with the customer’s needs is a cognitive task that customers will be unable to manage effectively. In this paper, we propose a hybrid knowledge-based recommender system that assists customers in selecting previously customized PSS variants from a wide range of available ones. The recommender system (RS) utilizes ontologies for capturing customer requirements, as well as product-service and production-related knowledge. The RS follows a hybrid recommendation approach, in which the problem of selecting previously customized PSS variants is encoded as a constraint satisfaction problem (CSP), to filter out PSS variants that do not satisfy customer needs, and then uses a weighted utility function to rank the remaining PSS variants. Finally, the RS offers a list of ranked PSS variants that can be scrutinized by the customer. In this study, the proposed recommendation approach was applied to a real-life large-scale case study in the domain of laser machines. To ensure the applicability of the proposed RS, a web-based prototype system has been developed, realizing all the modules of the proposed RS.

scholarly journals Permutation groups with small orbit growth

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Manuel Bodirsky ◽  
Bertalan Bodor
Keyword(s):  
Automorphism Group ◽  
Constraint Satisfaction ◽  
Constraint Satisfaction Problem ◽  
Permutation Groups ◽  
First Order ◽  
Finite Covers

Abstract Let K exp + \mathcal{K}_{{\operatorname{exp}}{+}} be the class of all structures 𝔄 such that the automorphism group of 𝔄 has at most c ⁢ n d ⁢ n cn^{dn} orbits in its componentwise action on the set of 𝑛-tuples with pairwise distinct entries, for some constants c , d c,d with d < 1 d<1 . We show that K exp + \mathcal{K}_{{\operatorname{exp}}{+}} is precisely the class of finite covers of first-order reducts of unary structures, and also that K exp + \mathcal{K}_{{\operatorname{exp}}{+}} is precisely the class of first-order reducts of finite covers of unary structures. It follows that the class of first-order reducts of finite covers of unary structures is closed under taking model companions and model-complete cores, which is an important property when studying the constraint satisfaction problem for structures from K exp + \mathcal{K}_{{\operatorname{exp}}{+}} . We also show that Thomas’ conjecture holds for K exp + \mathcal{K}_{{\operatorname{exp}}{+}} : all structures in K exp + \mathcal{K}_{{\operatorname{exp}}{+}} have finitely many first-order reducts up to first-order interdefinability.

scholarly journals System Modelling and Analysis to Support Economic Assessment of Product-Service Systems

Systems ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 6
Author(s):  
Khaled Medini ◽  
Sophie Peillon ◽  
Martha Orellano ◽  
Stefan Wiesner ◽  
Ang Liu
Keyword(s):  
Business Models ◽  
Economic Assessment ◽  
Service Industries ◽  
Service Systems ◽  
System Modelling ◽  
Value Network ◽  
A Value ◽  
Product Service ◽  
Industrial Cleaning ◽  
Product Service Systems

The evolution towards more customer-centric operations within manufacturing and service industries gave rise to novel ways of value creation and delivery such as Product–Service Systems (PSS). PSS integrate tangible and intangible elements to create new values for both customers and providers. Therefore, a close collaboration is required among various actors in a value network to co-create values towards win–win gains. For companies to keep up with this pace, new decision support tools are needed to accompany PSS engineering and to adjust business models. This need is confronted with the scarcity of PSS-oriented economic assessment models and methods. This paper presents a comprehensive framework for the economic assessment of PSS. The framework relies on a novel combination of system modelling and analysis approaches to enable cost and revenue attribution to different actors in a value network. The applicability and relevance of the framework are demonstrated through a case study in the industrial cleaning sector.

A Systematic Function Recommendation Process for Data-Driven Product and Service Design

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Zhinan Zhang ◽  
Ling Liu ◽  
Wei Wei ◽  
Fei Tao ◽  
Tianmeng Li ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Vital Role ◽  
Data Driven ◽  
Design Parameters ◽  
Sound Design ◽  
New Paradigm ◽  
Senior Managers ◽  
Product Service ◽  
Target User

This paper presents a systematic function recommendation process (FRP) to recommend new functions to an existing product and service. Function plays a vital role in mapping user needs to design parameters (DPs) under constraints. It is imperative for manufacturers to continuously equip an existing product/service with exciting new functions. Traditionally, functions are mostly formulated by experienced designers and senior managers based on their subjective experience, knowledge, creativity, and even heuristics. Nevertheless, against the sweeping trend of information explosion, it is increasingly inefficient and unproductive for designers to manually formulate functions. In e-commerce, recommendation systems (RS) are ubiquitously used to recommend new products to users. In this study, the practically viable recommendation approaches are integrated with the theoretically sound design methodologies to serve a new paradigm of recommending new functions to an existing product/service. The aim is to address the problem of how to estimate an unknown rating that a target user would give to a candidate function that is not carried by the target product/service yet. A systematic function → product recommendation process is prescribed, followed by a detailed case study. It is indicated that practically meaningful functional recommendations (FRs) can indeed by generated through the proposed FRP.

A performance prediction model for BIC-OFDM transmissions with AMC over nonlinear fading channels

2011 ◽  
Author(s):  
Filippo Giannetti ◽  
Ivan Stupia ◽  
Vincenzo Lottici ◽  
Riccardo Andreotti ◽  
Aldo N. D'Andrea ◽  
...  
Keyword(s):  
Prediction Model ◽  
Fading Channels ◽  
Performance Prediction ◽  
A Performance
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