In this paper, we study the re-entrant no-wait flexible flowshop scheduling problem with makespan minimization objective and then consider two parallel machines for each stage. The main characteristic of a re-entrant environment is that at least one job is likely to visit certain stages more than once during the process. The no-wait property describes a situation in which every job has its own ...

This paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. This problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life ti...

The aim of lot sizing problems is to determine the periods where production takes place and the quantities to be produced in order to satisfy the customer demand while minimizing the total cost. Due to its importance on the efficiency of the production and inventory systems, Lot sizing problems are one of the most challenging production planning problems and have been studied for many years wit...

The job-shop scheduling problem (JSSP) is well known as one of the most difficult NP-hard combinatorial optimization problems. Genetic Algorithms (GAs) for solving the JSSP have been proposed, and they perform well compared with other approaches [1]. However, the tuning of genetic parameters has to be performed by trial and error, making optimization by GA ad hoc. To address this problem, Sawai...

in this paper, a connecting rod was modeled and analyzed by finite element method. byusing genetic algorithm (ga) and modified cuckoo optimization algorithm (mcoa), the materialproperties and some geometrical specifications were optimized. cost function was a combination ofweight and stress. the connecting rod was under a load of 21.8 kn which obtained 360o crank angleat 5700 rev/min. the reduc...

in a large scale cyclic storage system ,as the number of rule parameters and/or number of operating period increase, general purpose gradient-based nlp solvers and/or genetic algorithms may loose their merits in finding optimally feasible solution to the problem. in these cases hybrid ga which decomposes the main problem into two manageable sub-problems with an iterative scheme between ga and l...

The problem of parallel and distributed function optimization with coevolutionary algorithms is considered. Two coevolutionary algorithms are used for this purpose and compared with sequential genetic algorithm (GA). The first coevolutionary algorithm called a loosely coupled genetic algorithm (LCGA) represents a competitive coevolutionary approach to problem solving and is compared with anothe...

In this paper we present several heuristic algorithms, including a Genetic Algorithm (GA), for obtaining polynomial threshold function (PTF) representations of Boolean functions (BFs) with small number of monomials. We compare these among each other and against the algorithm of Oztop [1] via computational experiments. The results indicate that our heuristic algorithms find more parsimonious rep...

Extinction has been frequently studied by evolutionary biologists and is shown to play a significant role in evolution. The genetic algorithm (GA), one of popular algorithms, based on key concepts natural evolution such as selection, crossover, mutation. Although GA widely implemented many fields, little work done enhance the performance through extinction. In this research, we propose stagnati...

Distance vector routing algorithms operate by having each router maintain a table giving the best known distance to each destination and which line to use to get there. Genetic algorithms are search algorithms based on mechanics of natural selection and natural genetics. To overcome some of the problems of traditional adaptive routing techniques genetic algorithms can be used. GA’s have the cap...