Heuristic Placement Routines For Two-Dimensional Rectangular Bin Packing Problems

In this study, we consider non-oriented and oriented cases of Two-Dimensional Rectangular Bin Packing Problems where a given set of small rectangles is packed without overlaps into a minimum number of identical large rectangles. In non-oriented case the rectangles are allowed to be rotated at 90° while the rectangles have fixed orientation in oriented case. We propose new heuristic placement routines called the Improved Lowest Gap Fill (LGFi) (for nonoriented case) and LG

A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

A two-dimensional cutting stock problem (2DCSP) needs to cut a set of given rectangular items from standard-sized rectangular materials with the objective of minimizing the number of materials used. This problem frequently arises in different manufacturing industries such as glass, wood, paper, plastic, etc. However, the current literatures lack a deterministic method for solving the 2DCSP. However, this study proposes a global method to solve the 2DCSP. It aims to reduce the number of binary variables for the proposed model to speed up the solving time and obtain the optimal solution. Our experiments demonstrate that the proposed method is superior to current reference methods for solving the 2DCSP

An effective placement method for the single container loading problem

© 2016 Elsevier Ltd. All rights reserved. This study investigates a three-dimensional single container loading problem, which aims to pack a given set of unequal-size rectangular boxes into a single container such that the length of the occupied space in the container is minimized. Motivated by the practical logistics instances in literature, the problem under study is formulated as a zero-one mixed integer linear programming model. Due to the NP-hardness of the studied problem, a simple but effective loading placement heuristic is proposed for solving large-size instances. The experimental results demonstrate that the developed heuristic is capable of solving the instances with more than two hundred boxes and more efficient than the state-of-the-art mixed integer linear program and existing heuristic methods

A simulation-based algorithm for solving the resource-assignment problem in satellite telecommunication networks

This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.En este trabajo se propone una heurística para la programación de las solicitudes de capacidad y la asignación periódica de los recursos de radio en las redes de satélites geoestacionarios (GEO) con topología en estrella, con la demanda de acceso múltiple de asignación (DAMA) de protocolo en la capa de enlace, y el Multi-Frequency Time Division (Acceso múltiple por MF-TDMA) y codificación y modulación Adaptable (ACM) en la capa física.En aquest treball es proposa una heurística per a la programació de les sol·licituds de capacitat i l'assignació periòdica dels recursos de ràdio en les xarxes de satèl·lits geoestacionaris (GEO) amb topologia en estrella, amb la demanda d'accés múltiple d'assignació (DAMA) de protocol en la capa d'enllaç, i el Multi-Frequency Time Division (Accés múltiple per MF-TDMA) i codificació i modulació Adaptable (ACM) a la capa física