Adaptive Local Search Approach for the Timetable Scheduling Problem

被引：0

作者：

Hadjidj, Drifa ^{[1
]}

Hadjidj, Rachid ^{[2
]}

Drias, Habiba ^{[3
]}

机构：

[1] UMBB, Fac Sci, Dept Informat, LIMOSE, Boumerdes, Algeria

[2] Qatar Univ, Coll Engn, CSE Dept, POB 2713, Doha, Qatar

[3] USTHB, Fac Genie Elect & Informat, Dept Informat, LRIA, Bab Ezzouar, Algeria

来源：

2017 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING - BOUMERDES (ICEE-B) | 2017年

关键词：

component: Scheduling; Timetable; Guided Local Search; Meta-heuristic; Graph heuristics; Aspiration strategy; Random moves strategy; ALGORITHM; GRAPH;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we present a new Adaptive Local Search approach (ALS) and its implementation for the NP hard Timetable Scheduling Problem. This approach uses graph heuristics to generate the initial solution and the Aspiration criterion with Random moves strategies to improve a guided local search procedure for the search process. Experimental results on a collection of data sets from the popular Carter's benchmark demonstrated very promising results when compared with several existing state of the art approaches.

引用

页数：6

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