A block-based evolutionary algorithm for flow-shop scheduling problem

Chang, Pei‐Chann; Chen, Menghui; Tiwari, Manoj Kumar; Iquebal, Ashif Sikandar

doi:10.1016/j.asoc.2013.07.018

Cited by 16 publications

(8 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The vehicle flow scheduling and job shop scheduling on land side up to yard and manufacturing industry respectively have been studied and shown to NP hard problem [11] [12]. We use the block based genetic algorithm to obtain the quay crane allocation.…”

Section: Methodsmentioning

confidence: 99%

“…Block Based Genetic Algorithm (BBGA) has been used to solve the hard complex problem of job shop scheduling [12]. In this technique, we develop the block of varying size of fit chromosomes and these fit schema from the building block of chromosomes for future generations.…”

Section: Block Based Genetic Algorithmmentioning

confidence: 99%

“…Once the blocks have been created, they are enrolled to generate the chromosomes for next generation. Chang et al [12] used the recombination function to create the chromosome, similarly we use the same function.…”

Section: Block Recombinationmentioning

confidence: 99%

See 2 more Smart Citations

The robust quay crane allocation for a discrete bulk material handling port

Pratap

Cheikhrouhou³

et al. 2015

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

View full text Add to dashboard Cite

This study investigates the quay crane allocation problem with respect to vessel assigned to a particular discrete berth at a bulk material handling port. In the proposed model, vessels at the anchorage are berthed on a First in first out (FIFO) basis at the port, and then the quay cranes are assigned to the berth dynamically before berthing and during unloading of the vessel. To solve the model, we used the Block Based Genetic Algorithm (BBGA) and Genetic Algorithm (GA). Computational study is conducted using the real data provided by a port located on the eastern coast of India.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Block Based Genetic Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

The robust quay crane allocation for a discrete bulk material handling port

Pratap

Cheikhrouhou³

et al. 2015

2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

View full text Add to dashboard Cite

show abstract

“…Some of researchers propose different forms of GA operators (Yan et al 2005) and others attempt to combine GA with other possible approaches like ACO (Lee 2004), PSO, etc. Some researchers implement a new evolutionary idea or combine some previous algorithms and idea to create a new method (Bonyadi et al 2007;Chang et al 2010Chang et al , 2013. In 2010, Chang et al (2010) first proposed an approach, namely artificial chromosomes for genetic algorithm (ACGA), which has been successful at injecting artificial chromosomes into the evolutionary process of the genetic algorithm and speeding up the convergence.…”

Section: Introductionmentioning

confidence: 99%

Imperial competitive algorithm with policy learning for the traveling salesman problem

Chen

Chang

2015

Soft Comput

Self Cite

View full text Add to dashboard Cite

The traveling salesman problem (TSP) is one of the most studied combinatorial optimization problems. In this paper, we present the new idea of combining the imperial competitive algorithm with a policy-learning function for solving the TSP problems. All offspring of each country are defined as representing feasible solutions for the TSP. All countries can grow increasingly strong by learning the effective policies of strong countries. Weak countries will generate increasingly excellent offspring by learning the policies of strong countries while retaining the characteristics of their own country. Imitating these policies will enable the weak countries to produce improved offspring; the solutions generated will, therefore, acquire a favorable scheme while maintaining diversity. Finally, experimental results for TSP instances from the TSP library have shown that our proposed algorithm can determine the salesman's tour with more effective performance levels than other known methods.

show abstract

“…There are also many researches for CVRP [5]- [7]. In addition, Tiwari [8] and Chang developed a block based [9], [10] recombination strategy for CVRP. The main idea is try to find the better route of one vehicle to recombine as complete solutions.…”

Section: Introductionmentioning

confidence: 99%

A hybrid two-stage sweep algorithm for capacitated vehicle routing problem

Chen

Chang

Chiu

et al. 2015

2015 International Conference on Control, Automation and Robotics

Self Cite

View full text Add to dashboard Cite

Capacitated Vehicle Routing Problem (CVRP) is a variant of Vehicle Routing Problem (VRP), where CVRP is only considered the capacity restrictions, and the object is to minimize the cost of the vehicles serve all customers. In this study, we proposed an approach which is hybrid two-phase sweep algorithm (SA) and greedy search for solving CVRP. At the first stage of SA, all customers are clustered by SA and define each cluster as a block. The second stage is to reconstruct each neighbour clusters based on the first stage. Then the greedy search is applied to minimize the cost of each vehicle. Finally, the computational result on standard instances show the proposed approach is effective. Keywords-capacitated vehicle routing problem; sweep algorithm; greedy search I. 978-1-4673-7523-8/15/$31.00 ©2015 IEEE

show abstract

A block-based evolutionary algorithm for flow-shop scheduling problem

Cited by 16 publications

References 15 publications

The robust quay crane allocation for a discrete bulk material handling port

The robust quay crane allocation for a discrete bulk material handling port

Imperial competitive algorithm with policy learning for the traveling salesman problem

A hybrid two-stage sweep algorithm for capacitated vehicle routing problem

Contact Info

Product

Resources

About