scholarly journals A Hybrid Simulated Annealing/Linear Programming Approach for the Cover Printing Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Federico Alonso-Pecina ◽  
David Romero
Keyword(s):  
Linear Programming ◽  
Simulated Annealing ◽  
Optimization Problem ◽  
Ad Hoc ◽  
Combinatorial Optimization Problem ◽  
Programming Approach ◽  
Printing Cost ◽  
Hybrid Simulated Annealing ◽  
Programming Techniques ◽  
Hard Cover

TheNP-hard cover printing problem addressed here consists in determining the number and composition of equal size impression grids, as well as the number of times each grid is printed, in order to fulfill the demand of different book covers at minimum total printing cost. The considered costs come from printing sheets and for composing grids. Thus, to deal with this combinatorial optimization problem we investigated two heuristics: one combines simulated annealing and linear programming techniques and the other is a hybrid of Tabu Search and an ad hoc procedure. Through intensive testing on available instances, these algorithms proved to be superior to previous approaches.

Matched Field Processing Based on the Simulated Annealing

2013 ◽  
Vol 651 ◽  
pp. 879-884
Author(s):  
Qi Wang ◽  
Ying Min Wang ◽  
Yan Ni Gou
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Mediterranean Sea ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Combinatorial Optimization Problem ◽  
Matched Field Processing ◽  
Combinatorial Optimization Problems ◽  
Passive Localization

The matched field processing (MFP) for localization usually needs to match all the replica fields in the observation sea with the received fields, and then find the maximum peaks in the matched results, so how to find the maximum in the results effectively and quickly is a problem. As known the classical simulated annealing (CSA) which has the global optimization capability is used widely for combinatorial optimization problems. For passive localization the position of the source can be recognized as a combinatorial optimization problem about range and depth, so a new matched field processing based on CSA is proposed. In order to evaluate the performance of this method, the normal mode was used to calculate the replica field. Finally the algorithm was evaluated by the dataset in the Mediterranean Sea in 1994. Comparing to the conventional matched field passive localization (CMFP), it can be conclude that the new one can localize optimum peak successfully where the output power of CMFP is maximum, meanwhile it is faster than CMFP.

Maximization of Platoon Formation Through Centralized Routing and Departure Time Coordination

2017 ◽  
Vol 2667 (1) ◽  
pp. 10-16 ◽  
Author(s):  
Vadim Sokolov ◽  
Jeffrey Larson ◽  
Todd Munson ◽  
Josh Auld ◽  
Dominik Karbowski
Keyword(s):  
Optimization Problem ◽  
Ad Hoc ◽  
Energy Savings ◽  
Aerodynamic Drag ◽  
Combinatorial Optimization Problem ◽  
High Rate ◽  
Fuel Savings ◽  
Vehicle To Vehicle ◽  
Road Capacity ◽  
Central Coordination

Platooning allows vehicles to travel with a small intervehicle distance in a coordinated fashion because of vehicle-to-vehicle connectivity. When applied at a larger scale, platooning creates significant opportunities for energy savings because of reduced aerodynamic drag, as well as increased road capacity and a reduction in congestion resulting from shorter vehicle headways. These potential savings are maximized, however, if platooning-capable vehicles spend most of their travel time within platoons. Ad hoc platoon formation may not ensure a high rate of platoon driving. This paper considers the problem of central coordination of platooning-capable vehicles. Coordination of their routes and departure times can maximize the fuel savings afforded by platooning vehicles. The resulting problem is a combinatorial optimization problem that considers the platoon coordination and vehicle routing problems simultaneously. The methodology is demonstrated through evaluation of the benefits of a coordinated solution and comparison with the uncoordinated case when platoons form only in an ad hoc manner. The coordinated and uncoordinated scenarios are compared on a grid network with various assumptions about demand and the time vehicles are willing to wait.

scholarly journals Global Inference for Sentence Compression: An Integer Linear Programming Approach

2008 ◽  
Vol 31 ◽  
pp. 399-429 ◽  
Author(s):  
J. Clarke ◽  
M. Lapata
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Optimization Problem ◽  
State Of The Art ◽  
Experimental Results ◽  
Global Constraints ◽  
Programming Approach ◽  
Linear Programming Approach ◽  
Sentence Compression ◽  
Global Inference

Sentence compression holds promise for many applications ranging from summarization to subtitle generation. Our work views sentence compression as an optimization problem and uses integer linear programming (ILP) to infer globally optimal compressions in the presence of linguistically motivated constraints. We show how previous formulations of sentence compression can be recast as ILPs and extend these models with novel global constraints. Experimental results on written and spoken texts demonstrate improvements over state-of-the-art models.

scholarly journals A Simulated Annealing Approach for the Train Design Optimization Problem

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Federico Alonso-Pecina ◽  
David Romero
Keyword(s):  
Simulated Annealing ◽  
Design Optimization ◽  
Optimization Problem ◽  
Ad Hoc ◽  
Heuristic Method ◽  
Combinatorial Problem ◽  
Second Step ◽  
Railway Network ◽  
Optimal Decisions ◽  
Initial Feasible Solution

The Train Design Optimization Problem regards making optimal decisions on the number and movement of locomotives and crews through a railway network, so as to satisfy requested pick-up and delivery of car blocks at stations. In a mathematical programming formulation, the objective function to minimize is composed of the costs associated with the movement of locomotives and cars, the loading/unloading operations, the number of locomotives, and the crews’ return to their departure stations. The constraints include upper bounds for number of car blocks per locomotive, number of car block swaps, and number of locomotives passing through railroad segments. We propose here a heuristic method to solve this highly combinatorial problem in two steps. The first one finds an initial, feasible solution by means of an ad hoc algorithm. The second step uses the simulated annealing concept to improve the initial solution, followed by a procedure aiming to further reduce the number of needed locomotives. We show that our results are competitive with those found in the literature.

Global Results Synthesis

2020 ◽  
pp. 165-175
Keyword(s):  
Linear Programming ◽  
Simulated Annealing ◽  
Tabu Search ◽  
Local Search ◽  
Constraint Programming ◽  
Cpu Time ◽  
Exact Approach ◽  
First Results ◽  
Programming Techniques ◽  
Portfolio Design

This chapter provides a global synthesis of the realized results by applying exact and approximate approaches on the portfolio design (PD) problem. The authors introduce an experimental analysis of best approaches based on linear programming and constraint programming techniques, according to the CPU time. Next, a global experiment synthesis of the best approximate approaches based on Simulated Annealing, IDWalk, Tabu Search, GWW, and VNS is realized according to the number of success and the CPU time. First results show that constraint programming with breaking all the detected symmetries is the best as an exact approach, VNS combined with simulated annealing is effective on non-trivial instances of the problem, and simulated annealing is the most effective as a simple local search.

Optimizing Gate Assignments at Airport

2014 ◽  
Vol 556-562 ◽  
pp. 4178-4184
Author(s):  
Pan Zheng ◽  
Jing Li ◽  
Ying Hui Liang
Keyword(s):  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Objective Function ◽  
Assignment Problem ◽  
Optimization Problem ◽  
High Efficiency ◽  
Heuristic Method ◽  
Combinatorial Optimization Problem ◽  
The Core ◽  
Gate Assignment

Airport gate assignment is to appoint a gate for the arrival or leave flight and to ensure that the flight is on schedule. Assigning the airport gate with high efficiency is a key task among the airport ground busywork. As the core of airport operation, aircraft gate assignment is known as a kind of complicated combinatorial optimization problem. In this paper, we consider the over-constrained Airport Gate Assignment Problem where the number of flights exceeds the number of gates available, and where the objective is to minimize the overall variance of slack time (OVST). According to the intrinsic characteristics of the objective function itself, we design a meta-heuristic method and simulated annealing to solve the problem. Finally, the illustrative examples show the validity of the proposed approach.

scholarly journals A linear programming approach to optimise the management of water in dammed river systems for meeting demands and preventing floods

2017 ◽  
Vol 18 (2) ◽  
pp. 713-722 ◽  
Author(s):  
Jaime Veintimilla-Reyes ◽  
Annelies De Meyer ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven
Keyword(s):  
Linear Programming ◽  
Water Availability ◽  
Distribution System ◽  
Network Flow ◽  
Water Distribution ◽  
Irrigated Agriculture ◽  
Programming Approach ◽  
Programming Techniques ◽  
Industrial Use ◽  
Spatio Temporal

Abstract Water in sufficient quantity and quality is indispensable for multiple purposes like domestic and industrial use, irrigated agriculture, hydropower generation and ecosystem functioning. In many regions of the world, water availability is limited and even declining. Moreover, water availability is variable in space and time and often does not match with the spatio-temporal demand pattern. To overcome the temporal discrepancy between availability and consumption, reservoirs are constructed. Monitoring and predicting the water available in the reservoirs, the needs of the consumers and the losses throughout the river and water distribution system are necessary requirements to fairly allocate the available water to the different users, prevent floods and ensure sufficient water flow in the river. In this paper, this surface water allocation problem is considered a Network Flow Optimisation Problem (NFOP) solved by spatio-temporal optimisation using linear programming techniques.

scholarly journals A Quality of Service (Qos) Load Balanced Hybrid Simulated Annealing -Stochastic Diffusion Search (Sa-Sds) Network Backbone for Manet

2021 ◽  
Author(s):  
KAVITHA V.R ◽  
Moorthi M
Keyword(s):  
Quality Of Service ◽  
Simulated Annealing ◽  
Ad Hoc ◽  
Dominating Set ◽  
Local Optimum ◽  
Mobile Nodes ◽  
Stochastic Diffusion ◽  
Hybrid Simulated Annealing ◽  
Stochastic Diffusion Search

Abstract The Mobile Ad hoc Networks (MANET) are those networks that do not have the infrastructure and are formed dynamically by means of an autonomous system of some mobile nodes connected through wireless links. All routers are left free to be able to randomly move and arbitrarily organize themselves. So, the wireless topology of the network can have unpredictable and rapid changes. In these types of networks, the provisioning of services based on Quality of Service (QoS) can pose to be very challenging. The work further presented a newer approach that was based on a hybrid Simulated Annealing (SA) along with a Stochastic Diffusion Search (SDS) based multi-path routing network which backbones in giving support to the enhanced QoS in the MANETs. This multipath routing had the objective of improving the dependability and the throughput along with load balancing. The SA is used for solving the problem of the Minimum Dominating Set (MDS). This SDS heuristic gives an algorithm which is simple in its structure and also provides a high exploration level along with fast convergence in comparison with the other algorithms. SA algorithms are also used for improving the diversity of agent and for avoiding it from being trapped within the local optimum. The results of the experiment proved that the SA-SDS method proposed had a better performance compared to the Connected Dominating Set (CDS)-SA.

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