This paper considers the allocation of maximum reliability to a complex system, while minimizing the cost of the system, a type of multi-objective optimization problem (MOOP). Multi-objective Evolutionary Algorithms (MOEAs) have been shown in the last few years as powerful techniques to solve MOOP .This paper successfully applies a Nondominated sorting genetic algorithm (NSGA-II) technique to o...

Reverse logistics, which is induced by various forms of used products and materials, has received growing attention throughout this decade. In a highly competitive environment, the service level is an important criterion for reverse logistics network design. However, most previous studies about product returns only focused on the total cost of the reverse logistics and neglected the service lev...

In this paper, a novel multi-objective orthogonal simulated annealing algorithm MOOSA using a generalized Pareto-based scale-independent fitness function and multi-objective intelligent generation mechanism (MOIGM) is proposed to efficiently solve multi-objective optimization problems with large parameters. Instead of generate-and-test methods, MOIGM makes use of a systematic reasoning ability ...

In this paper, we propose to mimic some well-known methods of control theory to automatically fix the parameters of a multi-objective Simulated Annealing (SA) method. Our objective is to allow a decision maker to efficiently use advanced operation research techniques without a deep knowledge of this domain. Classical SA controls the probability of acceptance using an a priori temperature schedu...

A personification heuristic Genetic Algorithm is established for the placement of digital microfluidics-based biochips, in which, the personification heuristic algorithm is used to control the packing process, while the genetic algorithm is designed to be used in multi-objective placement results optimizing. As an example, the process of microfluidic module physical placement in multiplexed in-...

-We formalize clustering as a partitioning problem with a user-defined internal clustering criterion and present SINICC, an unbiased, empirical method for comparing internal clustering criteria. An application to multi-sensor fusion is described, where the data set is composed of inexact sensor "reports" pertaining to "objects" in an environment. Given these reports, the objective is to produce...

The permutation flowshop scheduling problem with the objective of minimizing total flow time is known as a NP-hard problem, even for the two-machine cases. Because of the computational complexity of this problem, a multi-start simulated annealing (MSA) heuristic, which adopts a multi-start hill climbing strategy in the simulated annealing (SA) heuristic, is proposed to obtain close-to-optimal s...

-In this paper, multi-objective optimal placement (MOOP) of multi-type flexible AC transmission systems (FACTS) devices for Thailand power system is proposed. Four types of FACTS devices are used: thyristor-controlled series capacitor (TCSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC), and static var compensator (SVC). The problem is decomposed into the opti...

This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this probl...

This study presents the use and comparison of various bio-inspired algorithms for optimizing the response of a PID controller for a Brushless DC Motor in contrast to the conventional methods of tuning. For the optimization of the PID controllers Genetic Algorithm, Multi-objective Genetic Algorithm and Simulated Annealing have been used. PID controller tuning with soft-computing algorithms compr...