Using mixed integer programming models to synchronously determine production levels and market prices in an integrated market for roundwood and forest biomass

2013 ◽  
Author(s):  
Jiehong Kong ◽  
Mikael Rönnqvist ◽  
Mikael Frisk
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Forest Biomass ◽  
Programming Models ◽  
Mixed Integer ◽  
Market Prices

Mixed Integer Programming Models on Scheduling Automated Stacking Cranes

2021 ◽  
Vol 8 (4) ◽  
pp. 11-33
Author(s):  
Amir Gharehgozli ◽  
Orkideh Gharehgozli ◽  
Kunpeng Li
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Recent Trend ◽  
Container Terminals ◽  
Programming Models ◽  
Mixed Integer ◽  
Global Supply Chains ◽  
Objective Functions ◽  
Operational Constraints ◽  
Automated Stacking Cranes

Automated deep-sea container terminals are the main hubs to move millions of containers in today's global supply chains. Terminal operators often decouple the landside and waterside operations by stacking containers in stacks perpendicular to the quay. Traditionally, a single automated stacking cranes (ASC) is deployed at each stack to handle containers. A recent trend is to use new configurations with more than one crane to improve efficiency. A variety of new configurations have been implemented, such as twin, double, and triple ASCs. In this paper, the authors explore and review the mixed integer programming models that have been developed for the stacking operations of these new configurations. They further discuss how these models can be extended to contemplate diverse operational constraints including precedence constraints, interference constraints, and other objective functions.

scholarly journals Modelling Multi-Period Set-up Times in the Proportional Lot-Sizing Problem

2009 ◽  
Vol 3 (2) ◽  
pp. 15-35 ◽  
Author(s):  
Waldemar Kaczmarczyk
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Lot Sizing ◽  
Programming Models ◽  
Mixed Integer ◽  
Lot Sizing Problem ◽  
Set Up

This paper presents new mixed integer programming models for the Proportional Lot-Sizing Problem (PLSP) with set-up times longer than a period. Proposed models explicitly calculate the distribution of times amongst products in periods with a changeover and determine a final period for every set-up operation. Presented results prove that the proposed models are easier to solve using standard MIP methods than already known models.

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