scholarly journals Multiobjective Stochastic Programming for Mixed Integer Vendor Selection Problem Using Artificial Bee Colony Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Mostafa Ekhtiari ◽  
Shahab Poursafary
Keyword(s):  
Large Scale ◽  
Artificial Bee Colony ◽  
Imperialist Competitive Algorithm ◽  
Efficient Solutions ◽  
Mixed Integer ◽  
Vendor Selection ◽  
Stochastic Problem ◽  
Bee Colony ◽  
Deterministic Problem ◽  
First Time

It has been always critical and inevitable to select and assess the appropriate and efficient vendors for the companies such that all the aspects and factors leading to the importance of the select process should be considered. This paper studies the process of selecting the vendors simultaneously in three aspects of multiple criteria, random factors, and reaching efficient solutions with the objective of improvement. Thus, selecting the vendors is introduced in the form of a mixed integer multiobjective stochastic problem and for the first time it is converted by CCGC (min-max) model to a mixed integer nonlinear single objective deterministic problem. As the converted problem is nonlinear and solving it in large scale will be time-consuming then the artificial bee colony (ABC) algorithm is used to solve it. Also, in order to better understand ABC efficiency, a comparison is performed between this algorithm and the particle swarm optimization (PSO) and the imperialist competitive algorithm (ICA) and Lingo software output. The results obtained from a real example show that ABC offers more efficient solutions to the problem solving in large scale and PSO spends less time to solve the same problem.

scholarly journals Optimal Torpedo Scheduling

2018 ◽  
Vol 63 ◽  
pp. 955-986 ◽  
Author(s):  
Adrian Goldwaser ◽  
Andreas Schutt
Keyword(s):  
Large Scale ◽  
Benders Decomposition ◽  
Steel Production ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Hot Metal ◽  
Rail Network ◽  
Sulfur Level ◽  
First Time ◽  
Resource Capacity

We consider the torpedo scheduling problem in steel production, which is concerned with the transport of hot metal from a blast furnace to an oxygen converter. A schedule must satisfy, amongst other considerations, resource capacity constraints along the path and the locations traversed as well as the sulfur level of the hot metal. The goal is first to minimize the number of torpedo cars used during the planning horizon and second to minimize the time spent desulfurizing the hot metal. We propose an exact solution method based on Logic based Benders Decomposition using Mixed-Integer and Constraint Programming, which optimally solves and proves, for the first time, the optimality of all instances from the ACP Challenge 2016 within 10 minutes. In addition, we adapted our method to handle large-scale instances and instances with a more general rail network. This adaptation optimally solved all challenge instances within one minute and was able to solve instances of up to 100,000 hot metal pickups.

A comparative study of population-based algorithms for a political districting problem

Kybernetes ◽  
2017 ◽  
Vol 46 (1) ◽  
pp. 172-190 ◽  
Author(s):  
Eric Alfredo Rincón-García ◽  
Miguel Ángel Gutiérrez-Andrade ◽  
Sergio Gerardo de-los-Cobos-Silva ◽  
Roman Anselmo Mora-Gutiérrez ◽  
Antonin Ponsich ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Artificial Bee Colony ◽  
Population Based ◽  
Efficient Solutions ◽  
Computational Experiments ◽  
Musical Composition ◽  
Solution Quality ◽  
Content Type ◽  
Weighting Factors ◽  
Bee Colony

Purpose This paper aims to propose comparing the performance of three algorithms based on different population-based heuristics, particle swarm optimization (PSO), artificial bee colony (ABC) and method of musical composition (DMMC), for the districting problem. Design/methodology/approach In order to compare the performance of the proposed algorithms, they were tested on eight instances drawn from the Mexican electoral institute database, and their respective performance levels were compared. In addition, a simulated annealing-based (simulated annealing – SA) algorithm was used as reference to evaluate the proposed algorithms. This technique was included in this work because it has been used for Federal districting in Mexico since 1994. The performance of the algorithms was evaluated in terms of the quality of the approximated Pareto front and efficiency. Regarding solution quality, convergence and dispersion of the resulting non-dominated solutions were evaluated. Findings The results show that the quality and diversification of non-dominated solutions generated by population-based algorithms are better than those produced by Federal Electoral Institute’s (IFE’s) SA-based technique. More accurately, among population-based techniques, discrete adaptation of ABC and MMC outperform PSO. Originality/value The performance of three population-based techniques was evaluated for the districting problem. In this paper, the authors used the objective function proposed by the Mexican IFE, a weight aggregation function that seeks for a districting plan that represents the best balance between population equality and compactness. However, the weighting factors can be modified by political agreements; thus, the authors decided to produce a set of efficient solutions, using different weighting factors for the computational experiments. This way, the best algorithm will produce high quality solutions no matter the weighting factors used for a real districting process. The computational experiments proved that the proposed artificial bee colony and method of musical composition-based algorithms produce better quality efficient solutions than its counterparts. These results show that population-based algorithms can outperform traditional local search strategies. Besides, as far as we know, this is the first time that the method of musical composition is used for this kind of problems.

scholarly journals Artificial bee colony algorithm for economic load dispatch with wind power energy

2016 ◽  
Vol 13 (3) ◽  
pp. 347-360 ◽  
Author(s):  
Amin Safari ◽  
Davoud Sheibai
Keyword(s):  
Power Systems ◽  
Power System ◽  
Wind Power ◽  
Large Scale ◽  
Artificial Bee Colony ◽  
Economic Load Dispatch ◽  
Power Networks ◽  
Power Generator ◽  
Bee Colony ◽  
Wind Power Generator

This paper presents an efficient Artificial Bee Colony (ABC) algorithm for solving large scale economic load dispatch (ELD) problems in power networks. To realize the ELD, the valve-point loading effect, system load demand, power losses, ramp rate limits and prohibited operation zones are considered here. Simulations were performed on four different power systems with 3, 6, 15 and 40 generating units and the results are compared with two forms of power systems, one power system is with a wind power generator and other power system is without a wind power generator. The results of this study reveal that the proposed approach is able to find appreciable ELD solutions than those of previous algorithms.

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