Volume 3 : Issue 4, December 2014

Volume 3 (4); Dec 30, 2015 [XML]

Research Paper


SJMIE-3-4-47-51

Particle Swarm Optimization for Step Fixed Charge Transportation Problems

Lagzaie L.

Sci. J. Mech. Ind. Eng., 3(4): 47-51, 2015; pii:S238309801400007-3

ABSTRACT

The efficient integrated scheduling of production and distribution in a supply chain becomes a challenging problem as global companies move towards higher collaborative and competitive environments. The problem is to determine both production schedule and air transportation allocation in coordinated way. In order to solve the given problem, a genetic algorithm (GA) and a Differential evolution algorithm (DE) are developed. The two proposed algorithms have been examined and tested on randomly generated instances. The experimental results show that the effectiveness and robustness of the proposed DE algorithm are better than GA.Supply Chain Integration, Air Transportation, Template Genetic Algorithm,
Differential Evolution


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SJMIE_-3_4_52-58Meta-Heuristics for Integrated Scheduling of Production and Air Transportation

Taghaodi R., Molla-Alizadeh-Zavardehi S., Mahmoodi Rad A., Esfahani M. J.

Sci. J. Mech. Ind. Eng., 3(4): 52-58, 2015; pii:S238309801400008-3

ABSTRACT

In this paper, we consider the step fixed-charge transportation problem where is one of the most important problems in transportation research area. In the step fixed-charge transportation problem due to the step function structure of the objective function, we are faced with a ‘‘NP- hard’’ problem. To tackle such an NP-hard problem, we present Particle swarm optimization (PSO) and also with Genetic Algorithm (GA) to compare them. The obtained results show the proficiency of GSA comparison with GA.
Key Words:
Transportation Problem, Step Fixed Charge Transportation Problem, Particle Swarm Optimization, Genetic Algorithm.


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Last Updated (Thursday, 19 November 2015 12:12)