Large-scale controlled rounding using tabu search with strategic oscillation

1993 ◽  
Vol 41 (2) ◽  
pp. 69-84 ◽  
Author(s):  
James P. Kelly ◽  
Bruce L. Golden ◽  
Arjang A. Assad
Keyword(s):  
Tabu Search ◽  
Large Scale ◽  
Strategic Oscillation ◽  
Controlled Rounding

A New Solution Seed for Job Shop Scheduling Problem

2011 ◽  
Vol 110-116 ◽  
pp. 3899-3905
Author(s):  
Parviz Fattahi ◽  
Mojdeh Shirazi Manesh ◽  
Abdolreza Roshani
Keyword(s):  
Tabu Search ◽  
Large Scale ◽  
Production Management ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Np Hard ◽  
Shop Scheduling ◽  
Large Scale Problems

Scheduling for job shop is very important in both fields of production management and combinatorial optimization. Since the problem is well known as NP-Hard class, many metaheuristic approaches are developed to solve the medium and large scale problems. One of the main elements of these metaheuristics is the solution seed structure. Solution seed represent the coding structure of real solution. In this paper, a new solution seed for job shop scheduling is presented. This solution seed is compared with a famous solution seed presented for the job shop scheduling. Since the problem is well known as NP-Hard class, a Tabu search algorithm is developed to solve large scale problems. The proposed solution seed are examined using an example and tabu search algorithm.

Large-scale var optimization and planning by tabu search

1996 ◽  
Vol 39 (3) ◽  
pp. 195-204 ◽  
Author(s):  
Deqiang Gan ◽  
Qu Zhihua ◽  
Hongzhi Cai
Keyword(s):  
Tabu Search ◽  
Large Scale

scholarly journals A multi-start iterated tabu search algorithm for the multi-resource agent bottleneck generalized assignment problem

2019 ◽  
Vol 10 (1) ◽  
pp. 37-46
Author(s):  
Gülçin Bektur
Keyword(s):  
Tabu Search ◽  
Assignment Problem ◽  
Large Scale ◽  
Search Algorithm ◽  
Maximum Load ◽  
Mixed Integer ◽  
Generalized Assignment Problem ◽  
Generalized Assignment ◽  
Iterated Tabu Search ◽  
Resource Agent

In this study, a multi-resource agent bottleneck generalized assignment problem (MRBGAP) is addressed. In the bottleneck generalized assignment problem (BGAP), more than one job can be assigned to an agent, and the objective function is to minimize the maximum load over all agents. In this problem, multiple resources are considered and the capacity of the agents is dependent on these resources and it has minimum two indices. In addition, agent qualifications are taken into account. In other words, not every job can be assignable to every agent. The problem is defined by considering the problem of assigning jobs to employees in a firm. BGAP has been shown to be NP- hard. Consequently, a multi-start iterated tabu search (MITS) algorithm has been proposed for the solution of large-scale problems. The results of the proposed algorithm are compared by the results of the tabu search (TS) algorithm and mixed integer linear programming (MILP) model.

scholarly journals Hybrid particle swarm optimization and tabu search for the design of large-scale water distribution networks

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
José Eloim Silva de Macêdo ◽  
José Roberto Gonçalves de Azevedo ◽  
Saulo de Tarso Marques Bezerra
Keyword(s):  
Particle Swarm Optimization ◽  
Tabu Search ◽  
Water Distribution ◽  
Large Scale ◽  
Particle Swarm ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization

ABSTRACT Water distribution network (WDN) optimization has received special attention from various technicians and researchers, mainly due to its high costs of implementation, operation and maintenance. However, the low computational efficiency of most developed algorithms makes them difficult to apply in large-scale WDN design problems. This article presents a hybrid particle swarm optimization and tabu search (H-PSOTS) algorithm for WDN design. Incorporating tabu search (TS) as a local improvement procedure enables the H-PSOTS algorithm to avoid local optima and show satisfactory performance. Pure particle swarm optimization (PSO) and H-PSOTS algorithms were applied to three benchmark networks proposed in the literature: the Balerma irrigation network, the ZJ network and the Rural network. The hybrid methodology obtained good results when seeking an optimal solution and revealed high computational performance, making it a new option for the optimal design of real water distribution networks.

Sign in / Sign up

Export Citation Format

Share Document