An Experimentation System for Testing Bee Behavior Based Algorithm to Solving a Transportation Problem.
ABSTRACT This paper describes a system, called eTransport to solve a transportation problem. The system was applied in experiments
that test meta-heuristic algorithms for solving such optimization task. The engine of this system is based on a bee behavior
based algorithm, called KAPI, designed by the authors. In order to make a comparison of the results obtained by KAPI, the
Ants Colony System and Tabu Search algorithms were also applied. The eTransport simulator can generate real-life scenarios
on Google Maps, while configuring and running tested algorithms, and finally, displaying the solutions found. Some illustrative
examples of experiments are presented and discussed. The analysis of results of multi-scenario simulations shows the advantages
of the KAPI algorithm, and justifies the conclusion that KAPI is much better and more effectiveat finding solutions to problems
of this kind than other known algorithms.
- SourceAvailable from: prolog.univie.ac.at[show abstract] [hide abstract]
ABSTRACT: This article addresses the well-known Capacitated Vehicle Routing Problem (CVRP), in the special case where the demand of a customer consists of a certain number of two-dimensional weighted items. The problem calls for the minimization of the cost of transportation needed for the delivery of the goods demanded by the customers, and carried out by a fleet of vehicles based at a central depot. In order to accommodate all items on the vehicles, a feasibility check of the two-dimensional packing (2L) must be executed on each vehicle. The overall problem, denoted as 2L-CVRP, is NP-hard and particularly difficult to solve in practice. We propose a Tabu Search algorithm, in which the loading component of the problem is solved through heuristics, lower bounds, and a truncated branch-and-bound procedure. The effectiveness of the algorithm is demonstrated through extensive computational experiments. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008Networks 12/2007; 51(1):4 - 18. · 0.65 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: In multicomputers and computer networks a proper allocation of incoming jobs has a big impact on efficiency of parallel and distributed computing. In this paper, the mesh topology and processor allocation with using First Fit (FF) and Stack-Based (SBA) schemes, are considered. The algorithms proposed by authors SSBA (Stack-Based with Sorting) and BFSBA (Better Fit Stack-Based) are described and analyzed. Evaluation of algorithm’s properties has been done with using the proposed experimentation system. This system consists of such modules like experiment design, visualization of allocation processes, presentation of results of series of experiments for the introduced measures of efficiency. The investigations, carried out in this system, show advantages of the proposed algorithms.Computational Science and Its Applications - ICCSA 2006, International Conference, Glasgow, UK, May 8-11, 2006, Proceedings, Part V; 01/2006
- [show abstract] [hide abstract]
ABSTRACT: In this paper, a new algorithm, called CABI, is proposed for solving unbalanced transportation problem. The algorithm is based on the natural behavior of bees. The efficiency of the algorithm was evaluated and compared to another implemented algorithm based on well-known Tabu Search approach. The investigations have been made using an advanced computer simulation system designed and implemented by the authors. In the paper, some examples of experiments are presented and discussed. The analysis of results of multi-aspects simulations shows advantages of CABI algorithm and justifies the conclusion that CABI seems to be promising for solving some kind of optimization problems.01/2010;