Optimisation of complex product innovation processes based on trend models with three-valued logic
This addresses optimization challenges in product innovation for industries, but appears incremental as it builds on existing trend-based modeling approaches.
The paper tackles the problem of optimizing complex product innovation processes by using trend models with three-valued logic to represent heuristics as simple trends, resulting in a solution defined as a set of scenarios with transitions depicted in a graph for predicting system behavior.
This paper investigates complex product-innovation processes using models grounded in a set of heuristics. Each heuristic is expressed through simple trends -- increasing, decreasing, or constant -- which serve as minimally information-intensive quantifiers, avoiding reliance on numerical values or rough sets. A solution to a trend model is defined as a set of scenarios with possible transitions between them, represented by a transition graph. Any possible future or past behaviour of the system under study can thus be depicted by a path within this graph.