Complexity Classification of Deterministic Scheduling Problems

AbstractA class of graphs is called monotone if it is closed under deletion of vertices and edges. Any such class may be defined in terms of forbidden subgraphs. The chromatic index of a graph is the smallest number of colors required for its edge-coloring such that any two adjacent edges have different colors. We obtain a complete classification of the complexity of the chromatic index problem for all monotone classes defined in terms of forbidden subgraphs having at most 6 edges or at most 7 vertices.

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Classification of Ship Routing and Scheduling Problems in Liner Shipping

INFOR Information Systems and Operational Research ◽

10.3138/infor.49.2.139 ◽

2011 ◽

Vol 49 (2) ◽

pp. 139-152 ◽

Cited By ~ 11

Author(s):

Karina H. Kjeldsen

Keyword(s):

Liner Shipping ◽

Scheduling Problems ◽

Ship Routing ◽

Routing And Scheduling ◽

Ship Routing And Scheduling

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Application and Evaluation of Bee-Based Algorithms in Scheduling

Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-5225-2944-6.ch002 ◽

2018 ◽

pp. 20-42

Author(s):

Ayse Aycim Selam ◽

Ercan Oztemel

Keyword(s):

Project Scheduling ◽

Optimal Solution ◽

Benchmark Problems ◽

Manufacturing Processes ◽

Scheduling Problems ◽

Hard Problems ◽

Project Scheduling Problem ◽

Multi Mode ◽

Vital Element

Scheduling is a vital element of manufacturing processes and requires optimal solutions under undetermined conditions. Highly dynamic and, complex scheduling problems can be classified as np-hard problems. Finding the optimal solution for multi-variable scheduling problems with polynomial computation times is extremely hard. Scheduling problems of this nature can be solved up to some degree using traditional methodologies. However, intelligent optimization tools, like BBAs, are inspired by the food foraging behavior of honey bees and capable of locating good solutions efficiently. The experiments on some benchmark problems show that BBA outperforms other methods which are used to solve scheduling problems in terms of the speed of optimization and accuracy of the results. This chapter first highlights the use of BBA and its variants for scheduling and provides a classification of scheduling problems with BBA applications. Following this, a step by step example is provided for multi-mode project scheduling problem in order to show how a BBA algorithm can be implemented.

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