Genetic algorithm solution for a risk-based partner selection problem in a virtual enterprise
Computers and Operations Research
Computers and Industrial Engineering
Using the analytic hierarchy process to rank foreign suppliers based on supply risks
Computers and Industrial Engineering
Research on Resource Selection with Precedence and Due Date Constraint
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Expert Systems with Applications: An International Journal
Supplier selection in electronic marketplaces using satisficing and fuzzy AHP
Expert Systems with Applications: An International Journal
Fusion of soft computing and hard computing for large-scale plants: a general model
Applied Soft Computing
A trust-based model using learning FCM for partner selection in the virtual enterprises
ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Expert Systems with Applications: An International Journal
Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)
Knowledge-Based Systems
Partner selection in a virtual enterprise under uncertain information about candidates
Expert Systems with Applications: An International Journal
A distributed decision making model for risk management of virtual enterprise
Expert Systems with Applications: An International Journal
Partner selection for renewable resources in construction supply chain
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Multi-objective decision-making methodology to create an optimal design chain partner combination
Computers and Industrial Engineering
| Hi-index | 0.01 |
Presents an investigation of how partner selection problems may be optimized by the use of a precedence network of subprojects. At the start, the problem is described by a model with the subscript type of variables and a non-analytical objective function. It cannot be solved by general mathematical programming methods. By using the fuzzy rule quantification method, a fuzzy logic-based decision-making approach for the project scheduling is proposed. We then develop a fuzzy decision embedded heuristic genetic algorithm (GA/FD) to find the solution for partner selection. The approach was demonstrated by the use of an experimental example drawn from a coal-fired power station construction project. The results show us that the suggested approach can quickly achieve the optimal solution for large-sized problems