Recently MOEA/D (multi-objective evolutionary algorithm based on decomposition) was proposed as a high-performance EMO (evolutionary multiobjective optimization) algorithm. MOEA/D has high search ability as well as high computational efficiency. Whereas other EMO algorithms usually do not work well on many-objective problems with four or more objectives, MOEA/D can properly handle them. This is...

The performance of information retrieval systems (IRSs) is usually measured using two different criteria, precision and recall. Precision is the ratio of the relevant documents retrieved by the IRS in response to a user’s query to the total number of documents retrieved, whilst recall is the ratio of the number of relevant documents retrieved to the total number of relevant documents for the us...

Abstract Nondominated Neighbor Immune Algorithm (NNIA) is proposed for multiobjective optimization by using a novel nondominated neighbor-based selection technique, an immune inspired operator, two heuristic search operators, and elitism. The unique selection technique of NNIA only selects minority isolated nondominated individuals in the population. The selected individuals are then cloned pro...

The use of Surrogate Based Optimization (SBO) is widely spread in engineering design to reduce the number of computational expensive simulations. However, “real-world” problems often consist of multiple, conflicting objectives leading to a set of competitive solutions (the Pareto front). The objectives are often aggregated into a single cost function to reduce the computational cost, though a b...

This paper studies the unrelated parallel machine scheduling problem with three minimization objectives – makespan, maximum earliness, and maximum tardiness (METUPMSP). The last two objectives combined are related to just-intime (JIT) performance of a solution. Three hybrid algorithms are presented to solve the MET-UPMSP: reactive GRASP with path relinking, dual-archived memetic algorithm (DAMA...

New multimedia embedded applications are increasingly dynamic, and rely on dynamically-allocated data types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large searching space of possible DDTs implementations. That implies the minimization of embedded design variables (memory accesses, power consumption and memory usa...

New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large searching space of possible DDTs implementations. This results in the minimization of embedded design variables (memory accesses, power consumption and memory ...

Congestion pricing strategy has been recognized as an effective countermeasure in the practical field of urban traffic congestion mitigation. Despite the positive effects of congestion pricing, its implementation has faced problems. This paper investigates the issue of environmental equity in cordon pricing and a park-and-ride scheme. Although pollution decreases inside the cordon by implementa...

The group A Streptococcus (GAS) M1T1 clone emerged in the 1980s as a leading cause of epidemic invasive infections worldwide, including necrotizing fasciitis and toxic shock syndrome. Horizontal transfer of mobile genetic elements has played a central role in the evolution of the M1T1 clone, with bacteriophage-encoded determinants DNase Sda1 and superantigen SpeA2 contributing to enhanced virul...

This paper presented a new two-stage green supply chain network, in which includes two innovations. Firstly, it presents a new multi-objective model for a two-stage green supply chain problem that considers the amount o...