A genetic algorithm for two-stage transportation problem using priority-based encoding

Gen, Mitsuo; Altıparmak, Fulya; Lin, Lin

doi:10.1007/s00291-005-0029-9

Cited by 239 publications

(111 citation statements)

References 11 publications

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“…The major research content of accident rescue is how to timely master and comprehensively utilize the environment information to make decision on how to distribute various relief materials from multiple material storage and collection points to handout and sub-handout points in affected areas in an efficient and reliable way. Gen et al (2006) sets up a two-stage model considering the allocation of materials and opening of distribution centres, a priority based GA has been designed to solve the problem. Özdamar and Demir (2012) establish a joint distribution mathematical model with relief materials first and the wounded people second, which aims at minimizing the transportation time and maximizing the utilization of resources.…”

Section: Introductionmentioning

confidence: 99%

A two-stage priority-based MOGA for materials allocation and loading problem in large-scale emergencies

2016

Revista de la Facultad de Ingeniería

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Reasonable allocation and reliable delivery of rescue materials are of vital importance in large-scale emergency relief operations. Aiming at lower the average completion time, lower overall risk and higher utilization of transportation resources, this paper sets up a multi-objective model based on the problem of direct distribution of various relief materials from multiple supply points to multiple demand points in the affected areas considering quantity constraints of materials and available vehicles in each supply points, as well as considering capacity and volume constraints of each kinds of vehicles. A two-stage priority based MOGA algorithm has been designed to solve the problem. The experiment shows that this algorithm is fast and reliable, and has high practicability.

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Section: Introductionmentioning

confidence: 99%

A two-stage priority-based MOGA for materials allocation and loading problem in large-scale emergencies

2016

Revista de la Facultad de Ingeniería

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“…During the time, GA is modified and hybridised with various algorithms in order to improve its search quality (Jaramillo et al, 2002). Among of which, pGA, proves useful in designing the SC (Mitsuo et al 2006). It is noteworthy that pGA is superior to Spanning Tree-based GA by using a simpler decoding procedure to generate random feasible chromosomes.…”

Section: Literature Reviewmentioning

confidence: 99%

“…After simplified, the LSC is encoded by the pGA procedure as in study of Mitsuo et al (2006) to identify its optimal configuration. The 5-tier SC is encoded through a 7-substring chromosome, in which the first, second and third substrings contain binary variables (open/close plants, DC and WH).…”

Section: Lsc Transformationmentioning

confidence: 99%

New Strategy to Optimize Lean Supply Chain Design by Meta-Heuristic

Nguyen¹,

Dao²

2017

American Journal of Engineering and Applied Sciences

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This paper aims at presenting one novel quantitative strategy of optimizing the design of Lean supply chain using Meta-Heuristics. While classifying Lean Manufacturing tools in two categories, namely Functional and Tier Lean tools, we propose a new framework to design the Lean supply chain by implementing the former into a 5-echelon Fat supply chain. As the following step, we investigate the effect of the latter on the mentioned Lean supply chain model. Then, we utilize the tight correlation of Tier Lean tools and priority-based Genetic Algorithm Meta-Heuristics in order to optimize the configuration of the Lean supply chain. Finally, these ideas are illustrated step by step in one numeral example.

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“…In this paper, we apply a priority-based genetic algorithm to solve model by Gen et al (2006). Different from the basic GA scheme, we apply a priority approach in GA, which not only considers position of gen in chromosome but also considers value of gen in its inside.…”

Section: Priority-based Genetic Algorithmsmentioning

confidence: 99%

Reliable multi period multi product supply chain design with facility disruption

Rafiei¹,

Mohammadi²,

Torabi³

2013

10.5267/j.dsl

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This paper presents a strategic multi segment, multi period and multi-product supply chain management to meet reliable networks for handling disruptions strike. We present a mixedinteger programming model whose objective is to minimize the expected cost composed of probability and cost of occurrence in each scenario. The proposed model of this paper considers time value of money for each operation and transportation cost. We attempt to minimize expected costs by considering the levels of inventory, back-ordering, the available machine capacity and labor levels for each source, transportation capacity at each transshipment node and available warehouse space at each destination. The problem is generalized by taking into account backup supplier with reserved capacity and backup transshipment node that, which satisfies demands at higher price without disruption facility. We use a priority-based genetic algorithms encoding to solve the proposed problem under multi period and multi product conditions. The performance of the proposed model is examined using some instances.

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A genetic algorithm for two-stage transportation problem using priority-based encoding

Cited by 239 publications

References 11 publications

A two-stage priority-based MOGA for materials allocation and loading problem in large-scale emergencies

A two-stage priority-based MOGA for materials allocation and loading problem in large-scale emergencies

New Strategy to Optimize Lean Supply Chain Design by Meta-Heuristic

Reliable multi period multi product supply chain design with facility disruption

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