In this study, for the loads supplied by three thermic plants, power of thermic plants, supplying the minimum values of the cost of energy used for an hour, have been found with Simulated Annealing (SA) which is a metaheuristic optimasition method. Firstly solution have been found with classical Lagrange Method. Later solution have also been found with SA algorithm. Solutions found with two dif...

In this paper a Simulated Annealing algorithm (SA) for solving the Protein Folding Problem (PFP) is presented. This algorithm has two phases: quenching and annealing. The first phase is applied at very high temperatures and the annealing phase is applied at high and low temperatures. The temperature during the quenching phase is decreased by an exponential function. We run through an efficient ...

The quadratic assignment problem (QAP) is one of the well-known combinatorial optimization problems and is known for its various applications. In this paper, we propose a modified simulated annealing algorithm for the QAP – M-SA-QAP. The novelty of the proposed algorithm is an advanced formula of calculation of the initial and final temperatures, as well as an original cooling schedule with osc...

In this paper, a novel adaptive fuzzy robust controller with a state observer approach based on the hybrid particle swarm optimization-simulated annealing (PSO-SA) technique for a class of multi-input multi-output (MIMO) nonlinear systems with disturbances is proposed. Firstly, particle swarm optimization-simulated annealing (PSO-SA) is used to adjust the fuzzy membership functions, while adapt...

Single row layout is one of the most usually used layout patterns in industries, particularly in flexible manufacturing systems. Here actual sequencing of machine and arrangement of parts, no doubt, have a great influence on the throughput of the flexible manufacturing system i.e., (F.M.S). This paper discusses the single row layout design in flexible manufacturing system (F.M.S). This paper fu...

In this paper, six different approaches using genetic algorithms (GA) and/or simulated annealing (SA) with improved bottom left (I-BL) algorithm [1] were applied for solution of two dimensional non-guillotine cutting problems. As examples, test problems including 29 individual rectangular pieces were used [2]. Performances of hybrid approaches on solutions of cutting problems were compared. Due...

Simulated annealing (SA) algorithm is a popular intelligent optimisation algorithm, but its efficiency is unsatisfactory. To improve its efficiency, this paper presents a swarm SA (SSA) algorithm by exploiting the learned knowledge from searching history. In SSA, a swarm of individuals run SA algorithm collaboratively. Inspired by ant colony optimisation (ACO) algorithm, SSA stores knowledge in...

In [6] solutions for the nesting problem are produced using the No Fit Polygon (NFP), simulated annealing (SA) and a new evaluation method. It showed that SA could out perform hill climbing, thus suggesting that evolutionary approaches produce better solutions than a standard search algorithm. In this paper this work is developed. Genetic algorithms (GA) and tabu search (TS) are compared with t...

In this paper, we study the unrelated parallel machine problem for minimizing the makespan, which is NP-hard. We used Simulated Annealing (SA) and Tabu Search (TS) with Neighborhood Search (NS) based on the structure of the problem. We also used a modified SA algorithm, which gives better results than the traditional SA and developed an effective heuristic for the problem: Squeaky Wheel Optimiz...

The simulated annealing (SA) algorithm [14] [5] has been applied to every di cult optimization problem in VLSI CAD. Existing SA implementations use monotone decreasing, or cooling, temperature schedules motivated by the algorithm's proof of optimality as well as by an analogy with statistical thermodynamics. This paper gives strong evidence that challenges the correctness of using such schedule...