Search results for "Metaheuristic"

Determining the best shipper sizes for sending products to customers

2014

A distribution company has to send products, packed into shippers, from the warehouse to retail shops. The number of different shipper types is regarded as a parameter given by the user, who is looking for a balance between transportation costs and stock and procurement costs. The problem is to decide the sizes of the shipper types to keep at the warehouse so as to minimize the cost of meeting the forecasted demand over the planning horizon. In this paper, we describe an integer linear programming formulation for the problem and obtaining feasible solutions. Other models, based on multiknapsack and p-median and facility location models, are for obtaining lower bounds. We study several ways …

The Chinese Postman Problem with Load-Dependent Costs

2018

[EN] We introduce an interesting variant of the well-known Chinese postman problem (CPP). While in the CPP the cost of traversing an edge is a constant (equal to its length), in the variant we present here the cost of traversing an edge depends on its length and on the weight of the vehicle at the moment it is traversed. This problem is inspired by the perspective of minimizing pollution in transportation, since the amount of pollution emitted by a vehicle not only depends on the travel distance but also on its load, among other factors. We define the problem, study its computational complexity, provide two mathematical programming formulations, and propose two metaheuristics for its soluti…

Scatter Search and Path Relinking: Foundations and Advanced Designs

2004

Scatter Search and its generalized form Path Relinking, are evolutionary methods that have been successfully applied to hard optimization problems. Unlike genetic algorithms, they operate on a small set of solutions and employ diversification strategies of the form proposed in Tabu Search, which give precedence to strategic learning based on adaptive memory, with limited recourse to randomization. The fundamental concepts and principles were first proposed in the 1970s as an extension of formulations, dating back to the 1960s, for combining decision rules and problem constraints. (The constraint combination approaches, known as surrogate constraint methods, now independently provide an impo…

Heuristics and meta-heuristics for 2-layer straight line crossing minimization

2003

AbstractThis paper presents extensive computational experiments to compare 12 heuristics and 2 meta-heuristics for the problem of minimizing straight-line crossings in a 2-layer graph. These experiments show that the performance of the heuristics (largely based on simple ordering rules) drastically deteriorates as the graphs become sparser. A tabu search metaheuristic yields the best results for relatively dense graphs, with a GRASP implementation as close second. Furthermore, the GRASP approach outperforms all other approaches when tackling low-density graphs.

New Heuristic Algorithms for the Windy Rural Postman Problem

2005

[EN] In this paper we deal with the windy rural postman problem. This problem generalizes several important arc routing problems and has interesting real-life applications. Here, we present several heuristics whose study has lead to the design of a scatter search algorithm for the windy rural postman problem. Extensive computational experiments over different sets of instances, with sizes up to 988 nodes and 3952 edges, are also presented. (c) 2004 Elsevier Ltd. All rights reserved.

Evolutionary Algorithms and Metaheuristics : Applications in Engineering Design and Optimization

2018

Tabu and Scatter Search for Artificial Neural Networks

2003

In this paper we address the problem of training multilayer feed-forward neural networks. These networks have been widely used for both prediction and classification in many different areas. Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been applied to solve this problem. This paper presents a new training algorithm based on the tabu search methodology that incorporates elements for search intensification and diversification by utilizing strategic designs where other previous approaches resort to randomization. Our method considers context and search information, as it is provided by th…

Hybrid prediction-optimization approaches for maximizing parts density in SLM of Ti6Al4V titanium alloy

2022

AbstractIt is well known that the processing parameters of selective laser melting (SLM) highly influence mechanical and physical properties of the manufactured parts. Also, the energy density is insufficient to detect the process window for producing full dense components. In fact, parts produced with the same energy density but different combinations of parameters may present different properties even under the microstructural viewpoint. In this context, the need to assess the influence of the process parameters and to select the best parameters set able to optimize the final properties of SLM parts has been capturing the attention of both academics and practitioners. In this paper differ…

Tabu search for min-max edge crossing in graphs

2020

Abstract Graph drawing is a key issue in the field of data analysis, given the ever-growing amount of information available today that require the use of automatic tools to represent it. Graph Drawing Problems (GDP) are hard combinatorial problems whose applications have been widely relevant in fields such as social network analysis and project management. While classically in GDPs the main aesthetic concern is related to the minimization of the total sum of crossing in the graph (min-sum), in this paper we focus on a particular variant of the problem, the Min-Max GDP, consisting in the minimization of the maximum crossing among all egdes. Recently proposed in scientific literature, the Min…

Cryptanalysis of Knapsack Cipher Using Ant Colony Optimization

2018

Ant Colony Optimization is a search metaheuristic inspired by the behavior of real ant colonies and shown their effectiveness, robustness to solve a wide variety of complex problems. In this paper, we present a novel Ant Colony Optimization (ACO) based attack for cryptanalysis of knapsack cipher algorithm. A Cipher-text only attack is used to discover the plaintext from the cipher-text. Moreover, our approach allows us to break knapsack cryptosystem in a minimum search space when compared with other techniques. Experimental results prove that ACO can be used as an effective tool to attack knapsack cipher.