A multi-objective sequencing problem and its mathematical formulation are described.
The proposed algorithm, MOSC (Multi-Objective Sequence Classifier), is compared to standard classifiers and previous works on these real data sets and exhibits noticeably better classification performance.
However, flexible computational tools for multi-objective sequence design are lacking, limiting the potential of these technologies.
D-Tailor presents significant differences to other multi-objective sequence optimization tools (Allert et al., 2010; Chung and Lee, 2012; Dana and Tuller, 2012; Gaspar et al., 2012; Raab et al., 2010; Racle et al., 2012; Salis et al., 2009).
data-centric multi objective QoS-aware routing protocol.
This study strives to minimize multi-objective flexible flowshop considering sequence-dependent setup times.
We developed D-Tailor as an extendable and flexible software platform for the multi-objective design of artificial sequences.
The framework is based on a sequence of multi-objective optimization scenarios and uses a genetic algorithm in combination with coupled building energy and daylighting simulations.
The first step sets initial clusters with their representatives, whereas the second step calculates the correct number of clusters by resolving a sequence of multi-objective multi-act sequential two-player games for conflict-clusters.
We then convert the equivalent multi-objective optimal control problem into a sequence of single-objective optimal switching control problems by using a modified normal boundary intersection method.
In this paper we present a new multi-objective floorplanning algorithm based on the sequence pair representation that can floorplan blocks in the form of islands.
