The paper considers the problem of maximizing the profits of a retailer operating in the Italian electricity market. The problem consists in selecting the contracts portfolio and in defining the bidding strategy in the wholesales market while respecting the technical and regulatory constraints. A novel solution method based on a enhanced discovery of the search domain in the simulated annealing...

Job Shop Scheduling Problem (JSSP) is an optimization problem in which ideal jobs are assigned to resources at particular times. In recent years many attempts have been made at the solution of JSSP using a various range of tools and techniques such as Branch and Bound and Heuristics algorithms. This paper proposed a new algorithm based on Genetic Algorithm (GA), Tabu Search (TS) and Simulated A...

The Vehicle Routing Problem (VRP) is an important management problem in the field of physical distribution and logistics. Good vehicle routing can not only increase the profit of logistics but also make logistics management more scientific. The Capacitated Vehicle Routing Problem (CVRP) constrained by the capacity of a vehicle is the extension of VRP. Our research applies a two-phase algorithm ...

A delivery problem which reduces to an NP-complete set-partitioning problem is considered. Two algorithms of parallel simulated annealing, i.e. the simultaneous independent searches and the simultaneous periodically interacting searches are investigated. The objective is to improve the accuracy of solutions to the problem by applying parallelism. The accuracy of a solution is meant as its proxi...

It is a long time that the Simulated Annealing (SA) procedure is introduced as a model-free optimization for solving NP-hard problems. Improvements from the standard SA in the recent decade mostly concentrate on combining its original algorithm with some heuristic methods. These modifications are rarely happened to the initial condition selection methods from which the annealing schedules start...

It is a long time that the Simulated Annealing (SA) procedure is introduced as a model-free optimization for solving NP-hard problems. Improvements from the standard SA in the recent decade mostly concentrate on combining its original algorithm with some heuristic methods. These modifications are rarely happened to the initial condition selection methods from which the annealing schedules start...

In this contribution we derive the cost function corresponding to the linear complexity Subtractive Interference Cancellation with tangent hyperbolic tentative decisions. We use the cost function to analyse the fix-points of solving the Subtractive Interference Cancellation equations. The analysis show that we can control the slope of the tangent hyperbolic functions so that the corresponding c...

In this paper, we demonstrate how simulated annealing algorithm can be applied to clustering algorithms used in ad hoc networks; specifically our recently proposed weighted clustering algorithm(WCA) is optimized by simulated annealing. As the simulated annealing stands to be a powerful stochastic search method, its usage for combinatorial optimization problems was found to be applicable in our ...

In this paper, we consider the convergence speed of mean field annealing (MFA). We combine MFA with microcanonical simulation(MCS) method and propose a new algorithm called microcanonical mean field annealing(MCMFA). In the proposed algorithm, cooling speed is controlled by current temperature so that computation in the MFA can be reduced without degradation of performance. In addition, the sol...

Since most sequencing problems are NP-hard, many heuristic techniques have been tried to solve such problems. In this paper, we investigate two methods Hopfield neural networks and Simulated Annealing and their application to the problem of placing standard cells during VLSI design. Comparisons were made with respect to solution quality and computing time. Simulated Annealing performed better i...