scholarly journals A VNS Metaheuristic with Stochastic Steps for Max 3-Cut and Max 3-Section

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Ai-fan Ling
Keyword(s):  
Heuristic Algorithm ◽  
Search Algorithm ◽  
Stochastic Search ◽  
Numerical Results ◽  
Approximate Algorithm ◽  
Local Search Algorithm ◽  
Neighborhood Structure ◽  
High Quality ◽  
Global Search Algorithm ◽  
Numerical Performance

A heuristic algorithm based on VNS is proposed to solve the Max 3-cut and Max 3-section problems. By establishing a neighborhood structure of the Max 3-cut problem, we propose a local search algorithm and a variable neighborhood global search algorithm with two stochastic search steps to obtain the global solution. We give some numerical results and comparisons with the well-known 0.836-approximate algorithm. Numerical results show that the proposed heuristic algorithm can obtain efficiently the high-quality solutions and has the better numerical performance than the 0.836-approximate algorithm for the NP-Hard Max 3-cut and Max 3-section problems.

scholarly journals Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations

2017 ◽  
Vol 70 (4) ◽  
pp. 699-718 ◽  
Author(s):  
Donggyun Kim ◽  
Katsutoshi Hirayama ◽  
Tenda Okimoto
Keyword(s):  
Distributed Algorithms ◽  
Search Algorithm ◽  
Real Data ◽  
Stochastic Search ◽  
Automatic Identification ◽  
Identification System ◽  
Local Search Algorithm ◽  
Ship Collision ◽  
Stochastic Search Algorithm ◽  
Made In

Ship collision avoidance involves helping ships find routes that will best enable them to avoid a collision. When more than two ships encounter each other, the procedure becomes more complex since a slight change in course by one ship might affect the future decisions of the other ships. Two distributed algorithms have been developed in response to this problem: Distributed Local Search Algorithm (DLSA) and Distributed Tabu Search Algorithm (DTSA). Their common drawback is that it takes a relatively large number of messages for the ships to coordinate their actions. This could be fatal, especially in cases of emergency, where quick decisions should be made. In this paper, we introduce Distributed Stochastic Search Algorithm (DSSA), which allows each ship to change her intention in a stochastic manner immediately after receiving all of the intentions from the target ships. We also suggest a new cost function that considers both safety and efficiency in these distributed algorithms. We empirically show that DSSA requires many fewer messages for the benchmarks with four and 12 ships, and works properly for real data from the Automatic Identification System (AIS) in the Strait of Dover.

scholarly journals An Enhanced Two-Level Metaheuristic Algorithm with Adaptive Hybrid Neighborhood Structures for the Job-Shop Scheduling Problem

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Pisut Pongchairerks
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Metaheuristic Algorithm ◽  
Local Search Algorithm ◽  
Perturbation Operator ◽  
Job Shop Scheduling Problem ◽  
Neighborhood Structure ◽  
Shop Scheduling ◽  
Upper Level

For solving the job-shop scheduling problem (JSP), this paper proposes a novel two-level metaheuristic algorithm, where its upper-level algorithm controls the input parameters of its lower-level algorithm. The lower-level algorithm is a local search algorithm searching for an optimal JSP solution within a hybrid neighborhood structure. To generate each neighbor solution, the lower-level algorithm randomly uses one of two neighbor operators by a given probability. The upper-level algorithm is a population-based search algorithm developed for controlling the five input parameters of the lower-level algorithm, i.e., a perturbation operator, a scheduling direction, an ordered pair of two neighbor operators, a probability of selecting a neighbor operator, and a start solution-representing permutation. Many operators are proposed in this paper as options for the perturbation and neighbor operators. Under the control of the upper-level algorithm, the lower-level algorithm can be evolved in its input-parameter values and neighborhood structure. Moreover, with the perturbation operator and the start solution-representing permutation controlled, the two-level metaheuristic algorithm performs like a multistart iterated local search algorithm. The experiment’s results indicated that the two-level metaheuristic algorithm outperformed its previous variant and the two other high-performing algorithms in terms of solution quality.

scholarly journals A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Tao Ren ◽  
Meiting Guo ◽  
Lin Lin ◽  
Yunhui Miao
Keyword(s):  
Local Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Flow Shop Scheduling ◽  
Release Dates ◽  
Scheduling Problem ◽  
Local Search Algorithm ◽  
High Quality ◽  
Shop Scheduling ◽  
Simulation Results

This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

scholarly journals Multi-Satellite Observation Scheduling Based on a Hybrid Ant Colony Optimization

2013 ◽  
Vol 765-767 ◽  
pp. 532-536 ◽  
Author(s):  
Ke Bin Gao ◽  
Guo Hua Wu ◽  
Jiang Han Zhu
Keyword(s):  
Local Search ◽  
Ant Colony Optimization ◽  
Search Algorithm ◽  
Graph Model ◽  
Satellite Observation ◽  
Ant Colony ◽  
Local Search Algorithm ◽  
Scheduling Problems ◽  
High Quality ◽  
Acyclic Directed Graph

in this paper, we attempted to find an effective method to resolve multi-satellite observation scheduling problems. Firstly, an acyclic directed graph model for multi-satellite observation scheduling was constructed. Secondly, based on the graph model, we presented a novel hybrid ant colony optimization mixed with the iteration local search algorithm (ACO-ILS) to produce high quality schedules. At last, extensive experimental simulations demonstrated that the proposed ACO-ILS algorithm is very efficient.

scholarly journals A Matheuristic Approach Combining Local Search and Mathematical Programming

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Carolina Lagos ◽  
Guillermo Guerrero ◽  
Enrique Cabrera ◽  
Stefanie Niklander ◽  
Franklin Johnson ◽  
...  
Keyword(s):  
Mathematical Programming ◽  
Local Search ◽  
Large Scale ◽  
Search Algorithm ◽  
Facility Location Problem ◽  
Specific Information ◽  
Local Search Algorithm ◽  
Capacitated Facility Location Problem ◽  
Capacitated Facility Location ◽  
Installation Cost

A novel matheuristic approach is presented and tested on a well-known optimisation problem, namely, capacitated facility location problem (CFLP). The algorithm combines local search and mathematical programming. While the local search algorithm is used to select a subset of promising facilities, mathematical programming strategies are used to solve the subproblem to optimality. Proposed local search is influenced by instance-specific information such as installation cost and the distance between customers and facilities. The algorithm is tested on large instances of the CFLP, where neither local search nor mathematical programming is able to find good quality solutions within acceptable computational times. Our approach is shown to be a very competitive alternative to solve large-scale instances for the CFLP.

Sign in / Sign up

Export Citation Format

Share Document