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.

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.

Equity and Strength in Stochastic Integer Programming Models for the Dynamic Single Airport Ground-Holding Problem

2020 ◽  
Vol 54 (4) ◽  
pp. 944-955 ◽  
Author(s):  
Alexander S. Estes ◽  
Michael O. Ball
Keyword(s):  
Integer Programming ◽  
Network Flow ◽  
Programming Model ◽  
Programming Models ◽  
Stochastic Integer Programming ◽  
Flow Problems ◽  
Proposed Model ◽  
Equity Property ◽  
Strong Formulation ◽  
Size Scales

We study stochastic integer programming models for assigning delays to flights that are destined for an airport whose capacity has been impacted by poor weather or some other exogenous factor. In the existing literature, empirical evidence seemed to suggest that a proposed integer programming model had a strong formulation, but no existing theoretical results explained the observation. We apply recent results concerning the polyhedra of stochastic network flow problems to explain the strength of the existing model, and we propose a model whose size scales better with the number of flights in the problem and that preserves the strength of the existing model. Computational results are provided that demonstrate the benefits of the proposed model. Finally, we define a type of equity property that is satisfied by both models.

Integrated Dispatching Model of Automated Lifting Vehicles, Quay Cranes and Yard Cranes at Automated Container Terminal

2014 ◽  
Vol 564 ◽  
pp. 678-683 ◽  
Author(s):  
Seyed Hamidreza Sadeghian ◽  
M.K.A.M. Ariffin ◽  
S.H. Tang ◽  
N. Ismail
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Container Terminal ◽  
Mixed Integer ◽  
Integer Programming Model ◽  
Mixed Integer Programming Model ◽  
Quay Cranes ◽  
Automated Container Terminal ◽  
Loading And Unloading

Integration of various types of handling equipment is one of the important methods to improve the efficiency of processes and productivity of a container terminal. Using ALVs, because of their ability in lifting a container from the ground by themselves, can reduce the delay of loading and unloading tasks in automatic container terminals.In this paper, a mixed-integer programming model, which considers the integration of ALVs, Quay Cranes and Yard Cranes, is developed. This model minimizes the makespan of the loading and unloading activities in an Automatic Container Terminal with limited buffer spaces.

Temporal and spatial harvesting of irregular systems of parcels

1996 ◽  
Vol 26 (6) ◽  
pp. 1079-1088 ◽  
Author(s):  
Stephanie Snyder ◽  
Charles ReVelle
Keyword(s):  
Integer Programming ◽  
Spatial Data ◽  
Programming Model ◽  
The United States ◽  
Simplex Algorithm ◽  
Programming Models ◽  
Mixed Integer ◽  
Central Position ◽  
Private Lands ◽  
Heuristic Solution

Spatial management issues have assumed a central position in planning for forest ecosystems in the United States on both public and private lands. The arrangement of management activities, especially harvesting activities, can often have adverse impacts on other neighboring areas of the forest. Thus, spatially explicit programming models, which can account for or prevent certain arrangements of activities or land allocations through the use of harvest adjacency constraints, have received considerable attention in the literature. The need for spatial specificity in programming models has led to the development of integer programming or mixed integer programming models. Given that integer programming problems are often viewed as a difficult class of problems to solve, heuristic solution methods have most often been used to solve spatially constrained forest management models. In this paper, a discrete (0–1) integer programming model that maximizes harvested timber volume over a multiperiod time horizon subject to harvest adjacency constraints is developed and tested for irregular, realistic systems of parcels. This model performed well computationally for many example configurations and was solved exactly using the simplex algorithm and limited branching and bounding. Certain spatial configurations with long time horizons did, however, require a nontrivial amount of branching and bounding. The model was tested using both contrived and real spatial data sets.

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.

Integer Programming Models for Sales Territory Alignment to Maximize Profit

1976 ◽  
Vol 13 (4) ◽  
pp. 426-430 ◽  
Author(s):  
Andris A. Zoltners
Keyword(s):  
Integer Programming ◽  
Mathematical Programming ◽  
Recent Article ◽  
Programming Model ◽  
Solution Procedure ◽  
Programming Models ◽  
Mathematical Programming Model ◽  
Heuristic Solution ◽  
Linear Integer Programming

A recent article described a mathematical programming model and heuristic solution procedure to realign sales territories. This report presents two linear integer programming models for sales territory alignment to maximize profit. Emphasis is placed on the development of models which are easy to implement.

scholarly journals On the periodic hierarchical Chinese postman problem

2021 ◽  
Author(s):  
Muhammed Emre Keskin ◽  
Chefi Triki
Keyword(s):  
Integer Programming ◽  
Time Horizon ◽  
Programming Model ◽  
Mathematical Formulation ◽  
General Purpose ◽  
Chinese Postman Problem ◽  
New Variant ◽  
Chinese Postman ◽  
High Level ◽  
First Time

AbstractThis paper presents a mathematical formulation and a heuristic approach for a new variant of the Hierarchical Chinese Postman Problem (HCPP). Indeed, we introduce the concept of periodicity, and we define and solve, for the first time, the Periodic-HCPP, denoted as P-HCPP. Given that the resulting integer programming model makes use of a big number of binary variables and given the extended time horizon considered, 30 days in our case, the problem is characterized by a high level of complexity. However, our developed heuristic is able to solve instances having up to 40 nodes, 520 arcs and 5 hierarchies, whereas a general-purpose solver like Gurobi was not able to provide solutions for instances having more than 10 nodes. While the collected results are very encouraging, we provide at the end of this paper a set of possible future extensions of this work.

The Gap Function: Evaluating Integer Programming Models over Multiple Right-Hand Sides

2021 ◽  
Author(s):  
Temitayo Ajayi ◽  
Christopher Thomas ◽  
Andrew J. Schaefer
Keyword(s):  
Linear Programming ◽  
Integer Programming ◽  
Optimization Problems ◽  
Programming Model ◽  
Programming Models ◽  
Linear Programming Relaxation ◽  
Gap Functions ◽  
Model Quality ◽  
Right Hand ◽  
The Right

For an integer programming model with fixed data, the linear programming relaxation gap is considered one of the most important measures of model quality. There is no consensus, however, on appropriate measures of model quality that account for data variation. In particular, when the right-hand side is not known exactly, one must assess a model based on its behavior over many right-hand sides. Gap functions are the linear programming relaxation gaps parametrized by the right-hand side. Despite drawing research interest in the early days of integer programming, the properties and applications of these functions have been little studied. In this paper, we construct measures of integer programming model quality over sets of right-hand sides based on the absolute and relative gap functions. In particular, we formulate optimization problems to compute the expectation and extrema of gap functions over finite discrete sets and bounded hyperrectangles. These optimization problems are linear programs (albeit of an exponentially large size) that contain at most one special ordered-set constraint. These measures for integer programming models, along with their associated formulations, provide a framework for determining a model’s quality over a range of right-hand sides.

Metaheuristic Search with Inequalities and Target Objectives for Mixed Binary Optimization – Part II

2012 ◽  
pp. 17-33
Author(s):  
Fred Glover ◽  
Saïd Hanafi
Keyword(s):  
Linear Programming ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Models ◽  
Mixed Integer ◽  
Solution Strategies ◽  
Diversification Strategies ◽  
Metaheuristic Search ◽  
New Inequalities

Recent metaheuristics for mixed integer programming have included proposals for introducing inequalities and target objectives to guide this search. These guidance approaches are useful in intensification and diversification strategies related to fixing subsets of variables at particular values. The authors’ preceding Part I study demonstrated how to improve such approaches by new inequalities that dominate those previously proposed. In Part II, the authors review the fundamental concepts underlying weighted pseudo cuts for generating guiding inequalities, including the use of target objective strategies. Building on these foundations, this paper develops a more advanced approach for generating the target objective based on exploiting the mutually reinforcing notions of reaction and resistance. The authors demonstrate how to produce new inequalities by “mining” reference sets of elite solutions to extract characteristics these solutions exhibit in common. Additionally, a model embedded memory is integrated to provide a range of recency and frequency memory structures for achieving goals associated with short term and long term solution strategies. Finally, supplementary linear programming models that exploit the new inequalities for intensification and diversification are proposed.

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