scholarly journals Empirical study of the greedy heuristic as applied to the link selection problem

2015 ◽  
Vol 7 (1) ◽  
pp. 107-120
Author(s):  
Pál Pusztai ◽  
Tamás Hajba
Keyword(s):  
Integer Programming ◽  
Road Network ◽  
Practical Problem ◽  
Original Problem ◽  
Selection Problem ◽  
Programming Models ◽  
Greedy Heuristic ◽  
License Plate ◽  
Computational Results ◽  
Binary Integer Programming

Abstract Behind the link selection problem there is a practical problem that aims to check efficiently the vehicles on a road network. The checking process is to be realized with license plate reading cameras for checking the valid vignette of vehicles using that part of the network. However this problem should be defined generally and the methods of obtaining a solution can be applied to a wider range of problems independent of the original problem. This paper defines the link selection problem with directed graph, it shows the NP-hard complexity and it gives a heuristic and binary integer programming models to solve the problem. These two kinds of approaches allow us to examine and qualify the heuristic. The computational results of the methods are compared with different sizes of problems.

scholarly journals Reshuffle minimisation to improve storage yard operations efficiency

2021 ◽  
Vol 15 ◽  
pp. 174830262199401
Author(s):  
Hammed Bisira ◽  
Abdellah Salhi
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Heuristic Approach ◽  
Container Terminals ◽  
Exact Method ◽  
Computational Results ◽  
Binary Integer Programming ◽  
Integer Programming Model ◽  
Compatibility Test ◽  
Storage Area

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.

scholarly journals Solution Strategies for a Multiport Container Ship Stowage Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Consuelo Parreño-Torres ◽  
Ramon Alvarez-Valdes ◽  
Francisco Parreño
Keyword(s):  
Integer Programming ◽  
Computational Analysis ◽  
Programming Model ◽  
Programming Models ◽  
Container Ship ◽  
Computational Results ◽  
Solution Strategies ◽  
Large Size ◽  
Loading And Unloading ◽  
First Time

The multiport container ship stowage problem consists in determining the position of the containers on board a ship along its route with the objective of minimizing the number of unproductive moves required in the loading and unloading operations at each port. This paper presents an integer programming model for the problem and proposes several sets of valid constraints that bring its LP-relaxation closer to an integer solution. Moreover, it presents a GRASP algorithm that generates stowage plans with a minimal number of unproductive moves in a high percentage of medium and large-size instances. An extended computational analysis has been performed in which, to the best of the authors’ knowledge, the efficiency of integer programming models for the problem is tested for the first time. With respect to GRASP, the computational results show that it performs well on different sized datasets.

The Rank-One Quadratic Assignment Problem

2020 ◽  
Author(s):  
Yang Wang ◽  
Wei Yang ◽  
Abraham P. Punnen ◽  
Jingbo Tian ◽  
Aihua Yin ◽  
...  
Keyword(s):  
Integer Programming ◽  
Assignment Problem ◽  
Computational Study ◽  
Quadratic Assignment Problem ◽  
Research Work ◽  
Programming Models ◽  
Quadratic Assignment ◽  
Computational Results ◽  
Special Cases ◽  
Rank One

In this paper, we study the quadratic assignment problem with a rank-one cost matrix (QAP-R1). Four integer-programming formulations are introduced of which three are assumed to have partial integer data. Unlike the standard quadratic assignment problem, some of our formulations can solve reasonably large instances of QAP-R1 with impressive running times and are faster than some metaheuristics. Pairwise relative strength of the LP relaxations of these formulations are also analyzed from theoretical and experimental points of view. Finally, we present a new metaheuristic algorithm to solve QAP-R1 along with its computational analysis. Our study offers the first systematic experimental analysis of integer-programming models and heuristics for QAP-R1. The benchmark instances with various characteristics generated for our study are made available to the public for future research work. Some new polynomially solvable special cases are also introduced. Summary of Contribution: This paper aims to advance our knowledge and ability in solving an important special case of the quadratic assignment problem. It shows how to exploit inherent properties of an optimization problem to achieve computational advantages, a strategy that was followed by researchers in model building and algorithm developments for decades. Our computational results attest to this time-tested general philosophy. The paper presents the first systematic computational study of the rank one quadratic assignment problem, along with new mathematical programming models and complexity analysis. We believe the theoretical and computational results of this paper will inspire further research on the topic and will be of significant value to practitioners using rank one quadratic assignment models.

Grammar-Based Integer Programming Models for Multiactivity Shift Scheduling

2011 ◽  
Vol 57 (1) ◽  
pp. 151-163 ◽  
Author(s):  
Marie-Claude Côté ◽  
Bernard Gendron ◽  
Louis-Martin Rousseau
Keyword(s):  
Integer Programming ◽  
Programming Models ◽  
Shift Scheduling

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.

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