Abstract: This paper addresses minimizing the makespan of the
distributed permutation flow shop scheduling problem. In this
problem, there are several parallel identical factories or flowshops
each with series of similar machines. Each job should be allocated to
one of the factories and all of the operations of the jobs should be
performed in the allocated factory. This problem has recently gained
attention and due to NP-Hard nature of the problem, metaheuristic
algorithms have been proposed to tackle it. Majority of the proposed
algorithms require large computational time which is the main
drawback. In this study, a general variable neighborhood search
algorithm (GVNS) is proposed where several time-saving schemes
have been incorporated into it. Also, the GVNS uses the sophisticated
method to change the shaking procedure or perturbation depending
on the progress of the incumbent solution to prevent stagnation of the
search. The performance of the proposed algorithm is compared to
the state-of-the-art algorithms based on standard benchmark
instances.
Abstract: Facility location is a complex real-world problem
which needs a strategic management decision. This paper provides a
general review on studies, efforts and developments in Facility
Location Problems which are classical optimization problems having
a wide-spread applications in various areas such as transportation,
distribution, production, supply chain decisions and
telecommunication. Our goal is not to review all variants of different
studies in FLPs or to describe very detailed computational techniques
and solution approaches, but rather to provide a broad overview of
major location problems that have been studied, indicating how they
are formulated and what are proposed by researchers to tackle the
problem. A brief, elucidative table based on a grouping according to
“General Problem Type” and “Methods Proposed” used in the studies
is also presented at the end of the work.
Abstract: This paper presents a comparison of metaheuristic
algorithms, Genetic Algorithm (GA) and Ant Colony Optimization
(ACO), in producing freeman chain code (FCC). The main problem
in representing characters using FCC is the length of the FCC
depends on the starting points. Isolated characters, especially the
upper-case characters, usually have branches that make the traversing
process difficult. The study in FCC construction using one
continuous route has not been widely explored. This is our
motivation to use the population-based metaheuristics. The
experimental result shows that the route length using GA is better
than ACO, however, ACO is better in computation time than GA.