scholarly journals Combinations of Some Shop Scheduling Problems and the Shortest Path Problem: Complexity and Approximation Algorithms

2015 ◽  
pp. 97-108 ◽  
Author(s):  
Kameng Nip ◽  
Zhenbo Wang ◽  
Wenxun Xing
Keyword(s):  
Approximation Algorithms ◽  
Shortest Path ◽  
Shortest Path Problem ◽  
Scheduling Problems ◽  
Problem Complexity ◽  
Shop Scheduling

scholarly journals Improved Approximation Algorithms for Shop Scheduling Problems

1994 ◽  
Vol 23 (3) ◽  
pp. 617-632 ◽  
Author(s):  
David B. Shmoys ◽  
Clifford Stein ◽  
Joel Wein
Keyword(s):  
Approximation Algorithms ◽  
Scheduling Problems ◽  
Shop Scheduling

scholarly journals The quadratic shortest path problem: complexity, approximability, and solution methods

2018 ◽  
Vol 268 (2) ◽  
pp. 473-485 ◽  
Author(s):  
Borzou Rostami ◽  
André Chassein ◽  
Michael Hopf ◽  
Davide Frey ◽  
Christoph Buchheim ◽  
...  
Keyword(s):  
Shortest Path ◽  
Shortest Path Problem ◽  
Problem Complexity ◽  
Solution Methods

scholarly journals A combination of flow shop scheduling and the shortest path problem

2013 ◽  
Vol 29 (1) ◽  
pp. 36-52 ◽  
Author(s):  
Kameng Nip ◽  
Zhenbo Wang ◽  
Fabrice Talla Nobibon ◽  
Roel Leus
Keyword(s):  
Shortest Path ◽  
Flow Shop ◽  
Shortest Path Problem ◽  
Flow Shop Scheduling ◽  
Shop Scheduling

scholarly journals A Combination of Flow Shop Scheduling and the Shortest Path Problem

2013 ◽  
Author(s):  
Kameng Nip ◽  
Zhenbo Wang ◽  
Fabrice Nobibon Talla ◽  
R. Leus
Keyword(s):  
Shortest Path ◽  
Flow Shop ◽  
Shortest Path Problem ◽  
Flow Shop Scheduling ◽  
Shop Scheduling

Approximation algorithms for shop scheduling problems with minsum objective: A correction

2006 ◽  
Vol 9 (6) ◽  
pp. 569-570 ◽  
Author(s):  
Wenhua Li ◽  
Maurice Queyranne ◽  
Maxim Sviridenko ◽  
Jinjiang Yuan
Keyword(s):  
Approximation Algorithms ◽  
Scheduling Problems ◽  
Shop Scheduling

A Primal Adjacency-Based Algorithm for the Shortest Path Problem with Resource Constraints

2020 ◽  
Vol 54 (5) ◽  
pp. 1153-1169
Author(s):  
Ilyas Himmich ◽  
Hatem Ben Amor ◽  
Issmail El Hallaoui ◽  
François Soumis
Keyword(s):  
Dynamic Programming ◽  
Shortest Path ◽  
Resource Constraints ◽  
Solution Space ◽  
Shortest Path Problem ◽  
Scheduling Problems ◽  
Least Cost Path ◽  
Major Drawback ◽  
Routing And Scheduling ◽  
Problem Instances

The shortest path problem with resource constraints (SPPRC) is often used as a subproblem within a column-generation approach for routing and scheduling problems. It aims to find a least-cost path between the source and the destination nodes in a network while satisfying the resource consumption limitations on every node. The SPPRC is usually solved using dynamic programming. Such approaches are effective in practice, but they can be inefficient when the network is large and especially when the number of resources is high. To cope with this major drawback, we propose a new exact primal algorithm to solve the SPPRC defined on acyclic networks. The proposed algorithm explores the solution space iteratively using a path adjacency–based partition. Numerical experiments for vehicle and crew scheduling problem instances demonstrate that the new approach outperforms both the standard dynamic programming and the multidirectional dynamic programming methods.

Flexible Job-Shop Scheduling Problems

2011 ◽  
pp. 234-263 ◽  
Author(s):  
Imed Kacem ◽  
Slim Hammadi ◽  
Pierre Borne
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Computing Time ◽  
Search Space ◽  
Scheduling Problems ◽  
Problem Complexity ◽  
Exact Methods ◽  
Shop Scheduling ◽  
Wire Routing ◽  
Np Complete

The Job-shop Scheduling Problem (JSP) is one of hardest problems; it is classified NP-complete (Carlier & Chretienne, 1988; Garey & Johnson, 1979). In the most part of cases, the combination of goals and resources can exponentially increase the problem complexity, because we have a very large search space and precedence constraints between tasks. Exact methods such as dynamic programming and branch and bound take considerable computing time (Carlier, 1989; Djerid & Portmann, 1996). Front to this difficulty, meta-heuristic techniques such as evolutionary algorithms can be used to find a good solution. The literature shows that they could be successfully used for combinatorial optimization such as wire routing, transportation problems, scheduling problems, etc. (Banzhaf, Nordin, Keller & Francone, 1998; Dasgupta & Michalewicz, 1997).

Approximation algorithms for shop scheduling problems with minsum objective

2002 ◽  
Vol 5 (4) ◽  
pp. 287-305 ◽  
Author(s):  
Maurice Queyranne ◽  
Maxim Sviridenko
Keyword(s):  
Approximation Algorithms ◽  
Scheduling Problems ◽  
Shop Scheduling
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