• Structural Engineering and Mechanics
• /
• v.45 no.2
• /
• pp.183-199
• /
• 2013

Current methods of analysis of trusses depend on matrix formulations based on equilibrium equations which are in fact derived from energy principles, and compatibility conditions. Recently it has been shown that the minimum energy principle, by itself, in its pure and unmodified form, can well be exploited to analyze structures when coupled with an optimization algorithm, specifically with a meta-heuristic algorithm. The resulting technique that can be called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) has already been applied to analyses of linear and nonlinear plane trusses successfully as coupled with simulated annealing and local search algorithms. In this study the technique is applied to both 2-dimensional and 3-dimensional trusses emphasizing robustness, reliability and accuracy. The trials have shown that the technique is robust in two senses: all runs result in answers, and all answers are acceptable as to the reliability and accuracy within the prescribed limits. It has also been shown that Harmony Search presents itself as an appropriate algorithm for the purpose.

• Journal of Navigation and Port Research
• /
• v.38 no.3
• /
• pp.299-305
• /
• 2014

In a ship-building, a transporter is the moving equipment to transport ship blocks from a workshop to another in a shipyard. The efficient scheduling of transporters has an important role for the operation of a building ship to be completed on schedule. There are the previous studies on the transporter scheduling for moving blocks in a shipyard. These studies have no consideration for the transporter combination to increase the productivity of moving blocks. This paper presents an efficient transporter scheduling model considering transporter combination explicitly. The objective of this model is to minimize the operational cost and maintain the workload balance among transporters. we also present three heuristics algorithms based on tabu search for finding the solution of the model. The efficiency of the proposed heuristics are verified with several computational tests.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.2
• /
• pp.168-175
• /
• 2003

A new algorithm based on Genetic Algorithms is proposed f3r solving process optimization problems formulated in MINLP, GDP and hybrid MINLP/GDP. This work is focused especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is experimented and many heuristics are adopted. Real and binary coded Genetic Algorithm initiates the global search in the entire search space and at every stage Simulated Annealing makes the candidates to climb up the local hills. Multi-Niche Crowding method is adopted as the multimodal function optimization technique. and the adaptation of probabilistic parameters and dynamic penalty systems are also implemented. New strategies to take the logical variables and constraints into consideration are proposed, as well. Various test problems selected from many fields of process systems engineering are tried and satisfactory results are obtained.

• Journal of Information Processing Systems
• /
• v.5 no.4
• /
• pp.237-242
• /
• 2009

The classical vehicle routing problem (VRP) can be extended by including customers who want to send goods to the depot. This type of VRP is called the vehicle routing problem with pickups and deliveries (VRPPD). This study proposes a novel way to solve VRPPD by introducing a two-phase heuristic routing algorithm which consists of a clustering phase and uses the geometrical center of a cluster and route establishment phase by applying a two-way search of each route after applying the TSP algorithm on each route. Experimental results show that the suggested algorithm can generate better initial solutions for more computer-intensive meta-heuristics than other existing methods such as the giant-tour-based partitioning method or the insertion-based method.

• Korean Management Science Review
• /
• v.23 no.3
• /
• pp.13-25
• /
• 2006

To reduce the signaling tost of paging in mobile communication, sequential paging schemes are proposed by partitioning a location area into several paging areas such that each area is paged sequentially. Necessary conditions for the optimal partition of cells with delay bound are examined by considering the mobiles location probability at each cell. The Optimal Cell Partitioning (OCP) is proposed based on the necessary conditions and the fathoming rule which trims off the unnecessary solution space and expedite the search process. Two Heuristics, BSG and BNC are also presented to further increase the computational efficiency in real-world paging scheme for the next generation mobile systems. The effectiveness of the 1)reposed paging schemes is illustrated with computational results. The Heuristic BSG that performs the search in the most promising solution group outperforms the best existing procedure with the 6-69% gain in paging cost in problems with 100 cells.

• Advances in Computational Design
• /
• v.1 no.1
• /
• pp.79-86
• /
• 2016

In this study, the three different meta-heuristics namely the Grey Wolf Optimizer (GWO), Stochastic Fractal Search (SFS), and Adaptive Differential Evolution with Optional External Archive (JADE) algorithms are examined. This study considers optimization of the planer frame to minimize its weight subjected to the strength and displacement constraints as per the American Institute of Steel and Construction - Load and Resistance Factor Design (AISC-LRFD). The GWO algorithm is associated with grey wolves' activities in the social hierarchy. The SFS algorithm works on the natural phenomenon of growth. JADE on the other hand is a powerful self-adaptive version of a differential evolution algorithm. A one-bay ten-story planar steel frame problem is examined in the present work to investigate the design ability of the proposed algorithms. The frame design is produced by optimizing the W-shaped cross sections of beam and column members as per AISC-LRFD standard steel sections. The results of the algorithms are compared. In addition, these results are also mapped with other state-of-art algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.48
• /
• pp.299-310
• /
• 1998

Actually mixed assembly line is mixed with open and close type workstation. This workstation is called hybridworkstation. The propose of this paper is to determine the sequencing of model that minimize line length for actual(hybridworkstation) mixed model assembly line. we developed three mathematical formulation of the problem to minimize the overall length of a line with hybrid station. Mathematical formulation classified model by operato schedule. Mixed model assembly line is combination program and NP-hard program. Thus computation time is often a critical factor in choosing a method of determining the sequence. This study suggests a tabu search technique which can provide a near optimal solution in real time and use the hill climbing heuristic method for selecting initial solution. Modified tabu search method is compared with MIP(Mixed Integer Program). Numerical results are reported to demonstrate the efficiency of the method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.1
• /
• pp.46-51
• /
• 1997

The optimal control of a continuous process has been performed using genetic algorithms(GAs). GAs are robust and easily applicable for complex and highly nonlinear problems. We introduce the heuristics 'dynamic range' which reduces the search space dramaticaly keeping the robust search of GAs. GAs with dynamic range show the better performance than SQP(Successive Quadratic Programing) method which converges to a local minimum. The proposed methology has been applied to the optimal control of the continuous MMA-VA copolymerization reactor for the production of the desired molecular wieght and the composition of VA in dead copolymer.

• Nuclear Engineering and Technology
• /
• v.53 no.11
• /
• pp.3772-3783
• /
• 2021

This work proposes a new efficient meta-heuristic optimization algorithm called Gamma Ray Interactions Based Optimization (GRIBO). The algorithm mimics different energy loss processes of a gamma-ray photon during its passage through a matter. The proposed novel algorithm has been applied to search for the global minima of 30 standard benchmark functions. The paper also considers solving real optimization problem in the field of nuclear engineering, radioisotope identification. The results are compared with those obtained by the Particle Swarm Optimization, Genetic Algorithm, Gravitational Search Algorithm and Grey Wolf Optimizer algorithms. The comparisons indicate that the GRIBO algorithm is able to provide very competitive results compared to other well-known meta-heuristics.

• The Journal of the Korea Contents Association
• /
• v.5 no.3
• /
• pp.193-199
• /
• 2005

One of the important fields for heuristics algorithm is how to balance between Intensificationand Diversification. Ant Colony System(ACS) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we propose Multi Colony Interaction Ant Model that achieves positive negative interaction through elite strategy divided by intensification strategy and diversification strategy to improve the performance of original ACS. And, we apply multi colony interaction ant model by this proposed elite strategy to TSP and compares with original ACS method for the performance.