scholarly journals MULTI-SITE PRODUCT CONFIGURATION OF TELECOMMUNICATION SWITCHES

2014 ◽  
pp. 101-107
Author(s):  
Alexander Felfernig ◽  
Gerhard Friedrich ◽  
Dietmar Jannach ◽  
Christian Russ ◽  
Markus Zanker
Keyword(s):  
Constraint Satisfaction ◽  
Business Case ◽  
Product Configuration ◽  
Problem Domain ◽  
Implementation Framework ◽  
Industrial Sectors ◽  
Distributed Problem Solving ◽  
Complex Solutions ◽  
Networked Economy ◽  
Configurable Products

Knowledge­based product configurators support their users in tailoring configurable products according to their specific demands and these systems have been successfully applied in many industrial sectors over the last decades. However, within today’s networked economy, the complex solutions of fered to the customers are in many cases assembled from configurable sub­products themselves. Within this paper we describe a business case where due to organisational and confidentiality reasons a single­configurator approach is not applicable and several configurators along the supply chain must cooperate in finding correct product configurations and in presenting them to an online customer. We present an algorithm based on Constraint Satisfaction that takes the specific characteristics of the problem domain into account and compare our approach to other work in the field of Distributed Problem Solving. The implementation framework for distributed configuration which is currently developed in the EU­funded project CAWICOMS1 is discussed in the final sections.

Towards a general ontology of configuration

1998 ◽  
Vol 12 (4) ◽  
pp. 357-372 ◽  
Author(s):  
TIMO SOININEN ◽  
JUHA TIIHONEN ◽  
TOMI MÄNNISTÖ ◽  
REIJO SULONEN
Keyword(s):  
Practical Experience ◽  
Product Configuration ◽  
Use Of Resources ◽  
New Concepts ◽  
Product Structures ◽  
General Ontology ◽  
And Function ◽  
Configurable Products ◽  
Constraint Sets

This article presents a generalized ontology of product configuration as a step towards a general ontology of configuration, which is needed to reuse and share configuration knowledge. The ontology presented consists of a set of concepts for representing the knowledge on a configuration and the restrictions on possible configurations. The ontology is based on a synthesis of the main approaches to configuration. Earlier approaches are extended with new concepts arising from our practical experience on configurable products. The concepts include components, attributes, resources, ports, contexts, functions, constraints, and relations between these. The main contributions of this work are in the detailed conceptualization of knowledge on product structures and in extending the resource concept with contexts for limiting the availability and use of resources. In addition, constraint sets representing different views on the product are introduced. The ontology is compared with the previous work on configuration. It covers all the principal approaches, that is, connection-based, structure-based, resource-based, and function-based approaches to configuration. The dependencies between the concepts arising from different conceptualizations are briefly analyzed. Several ways in which the ontology could be extended are pointed out.

scholarly journals The Business Case for Automating Data Management

2020 ◽  
Author(s):  
Mark Hobart
Keyword(s):  
Data Management ◽  
Fold Increase ◽  
Business Case ◽  
Regulatory Compliance ◽  
Quality Data ◽  
Efficiency Gains ◽  
Problem Domain ◽  
Management Tools ◽  
Information Governance ◽  
Business Data

Back in 2016, IDC forecast a ten-fold increase on business data processed globally by 2025. Combine this with increasing regulatory compliance and demand for quality data, then it is perhaps not a surprise to find that many businesses are feeling somewhat over-whelmed by the enormity of the data management and governance task they face. But, don’t despair, there is a compelling business case, both in terms of efficiency gains and tangible financial savings in adopting a strategy for centralising information governance and automating the management of your data. This paper will explore the emerging problem domain of data and look at the business case for use of automated data management tools to better prepare your organisation for the tsunami of data coming its way.

Social performance: key lessons from recent experiences within Shell

2005 ◽  
Vol 5 (3) ◽  
pp. 105-118 ◽  
Author(s):  
Titus Fossgard‐Moser
Keyword(s):  
Quantitative Research ◽  
Social Issues ◽  
Social Performance ◽  
Business Case ◽  
Effective Management ◽  
Policy Makers ◽  
Content Type ◽  
Governmental Organizations ◽  
Industrial Sectors ◽  
Non Governmental Organizations

PurposeSeeks to summarize the findings of research undertaken by the Shell Group to better understand the business relevance, parameters, status and tools and approaches to manage social performance.Design/methodology/approachThe paper is based on four detailed case studies that combined qualitative and quantitative research methodologies and included distinct operational, business and socio‐economic contexts. The paper seeks to build theory around the concept of social performance.FindingsKey findings include that: there exists a strong business case for social performance; good social performance is fundamentally concerned with the identification and management of core business impacts; social issues can be identified and managed in a systematic manner; and The Shell Group is developing and implementing a range of tools and approaches to assist effective management of social issues.Research limitations/implicationsThe research is based on a limited number of cases from within Shell; further validation of findings could be achieved through similar research in other industrial sectors.Practical implicationsResearch has highlighted the business case for social performance, key “ingredients” of social performance and provides a specific framework and tools for more effective management of social issues.Originality/valueFirst time such research has been undertaken within the Shell Group and perhaps similar companies. Paper should be of potential interest value to practitioners (e.g. social performance and CSR managers), academics, policy makers and non‐governmental organizations.

scholarly journals Distributed Problem Solving

AI Magazine ◽  
2012 ◽  
Vol 33 (3) ◽  
pp. 53 ◽  
Author(s):  
William Yeoh ◽  
Makoto Yokoo
Keyword(s):  
Problem Solving ◽  
Constraint Satisfaction ◽  
Optimization Problems ◽  
Constraint Satisfaction Problems ◽  
Constraint Optimization ◽  
Common Goal ◽  
Distributed Constraint Optimization ◽  
Distributed Constraint Satisfaction ◽  
Distributed Problem Solving ◽  
Constraint Optimization Problems

Distributed problem solving is a subfield within multiagent systems, where agents are assumed to be part of a team and collaborate with each other to reach a common goal. In this article, we illustrate the motivations for distributed problem solving and provide an overview of two distributed problem solving models, namely distributed constraint satisfaction problems (DCSPs) and distributed constraint optimization problems (DCOPs), and some of their algorithms.

Reasoning about conditional constraint specification problems and feature models

2011 ◽  
Vol 25 (2) ◽  
pp. 163-174 ◽  
Author(s):  
Raphael Finkel ◽  
Barry O'Sullivan
Keyword(s):  
Constraint Satisfaction ◽  
Directed Acyclic Graphs ◽  
Constraint Satisfaction Problems ◽  
Product Configuration ◽  
Feature Models ◽  
Model Builder ◽  
A Value ◽  
Acyclic Graphs ◽  
All Solutions ◽  
Constraint Specification

AbstractProduct configuration is a major industrial application domain for constraint satisfaction techniques. Conditional constraint satisfaction problems (CCSPs) and feature models (FMs) have been developed to represent configuration problems in a natural way. CCSPs are like constraint satisfaction problems (CSPs), but they also include potential variables, which might or might not exist in any given solution, as well as classical variables, which are required to take a value in every solution. CCSPs model, for example, options on a car, for which the style of sunroof (a variable) only makes sense if the car has a sunroof at all. FMs are directed acyclic graphs of features with constraints on edges. FMs model, for example, cell phone features, where utility functions are required, but the particular utility function “games” is optional, but requires Java support. We show that existing techniques from formal methods and answer set programming can be used to naturally model CCSPs and FMs. We demonstrate configurators in both approaches. An advantage of these approaches is that the model builder does not have to reformulate the CCSP or FM into a classic CSP, converting potential variables into classical variables by adding a “does not exist” value and modifying the problem constraints. Our configurators automatically reason about the model itself, enumerating all solutions and discovering several kinds of model flaws.

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