Flexible job shop scheduling problem (FJSP) is one of the hardest combinatorial optimization problems known to be NP-hard. This paper proposes a novel hybrid imperialist competitive algorithm with simulated annealing (HICASA) for solving the FJSP. HICASA explores the search space by using imperial competitive algorithm (ICA) and use a simulated annealing (SA) algorithm for exploitation in the s...

Concurrent computing can be applied to heuristic methods for combinatorial optimization to shorten computation time, or equivalently, to improve the solution when time is fixed. This paper presents several communication schemes for parallel simulated annealing, focusing on a combination of OpenMP nested in MPI. Strikingly, even though many publications devoted to either intensive or sparse comm...

This paper presents a hybrid genetic algorithm for the minimum linear arrangement problem. The algorithm was tested on a collection of 22 sparse graphs that has been used to test twelve other algorithms for the minimum linear arrangement problem. The graphs have up to 10,240 vertices and up to 49,820 edges. On about 2/3 of the graphs, our algorithm found solutions superior to all other algorith...

This paper attempts to overcome the local convergence problem of the Expectation Maximization (EM) based training of the Hidden Markov Model (HMM) in speech recognition. We propose a hybrid algorithm, Simulated Annealing Stochastic version of EM (SASEM), combining Simulated Annealing with EM that reformulates the HMM estimation process using a stochastic step between the EM steps and the SA. Th...

It is a long time that the Simulated Annealing (SA) procedure has been 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...

A New Hybrid Routing Algorithm based on Genetic and Simulated Annealing for Vehicular Ad hoc Networks

This research deals with a hybrid flow shop scheduling problem with parallel batching, machine eligibility, unrelated parallel machine, and different release dates to minimize the sum of the total weighted earliness and tardiness (ET) penalties. In parallel batching situation, it is supposed that number of machine in some stages are able to perform a certain number of jobs simultaneously. First...

In this paper, we present a complex distribution network design problem in supply chain system which includes location and inventory decisions. Customers’ demand is generated randomly and each distribution center maintains a certain amount of safety stock in order to achieve a certain service level for the customers it services. Unlike most of past research, our model allows for multiple levels...

The permutation flow shop scheduling problem (PFSP) is one of the most well known and well studied production scheduling problems with strong industrial background. Most scheduling problems are combinatorial optimization problems which are too difficult to be solved optimally, and hence heuristics are used to obtain good solutions in a reasonable time. The specific goal of this paper is to inve...