Metaheuristic approaches based on neighborhood search escape local optimality by applying predefined rules and constraints, such as tabu restrictions (in tabu search), acceptance criteria (in simulated annealing), and shaking (in VNS). We propose a general approach that attempts to learn (offline) the guiding constraints that, when applied online, will result in effective escape directions from...

In this article we investigate a new variant of Variable Neighborhood Search (VNS): Relaxation Guided Variable Neighborhood Search. It is based on the general VNS scheme and a new Variable Neighborhood Descent (VND) algorithm. The ordering of the neighborhood structures in this VND is determined by solving relaxations of them. The objective values of these relaxations are used as indicators for...

Local search heuristics are among the most popular approaches to solve hard optimization problems. Among them, Very Large Scale Neighborhood Search techniques present a good balance between the quality of local optima and the time to search a neighborhood. We develop a language to generate exponentially large neighborhoods for sequencing problems using grammars. We develop efficient generic dyn...

In this paper we introduce an hybrid evolutionary algorithm for computer-aided orchestration. Our current approach to orchestration consists in replicating a target sound with a set of instruments sound samples. We show how the orchestration problem can be viewed as a multi-objective 0/1 knapsack problem, with additional constraints and a case-specific criteria formulation. Our search method hy...

In this paper, three solutions for scheduling problem of the Single-Load and Multi-Load Automated Guided Vehicles (AGVs) in Container Terminals are proposed. The problem is formulated as Constraint Satisfaction and Optimization. When capacity of the vehicles is one container, the problem is a minimum cost flow model. This model is solved by the highest performance Algorithm, i.e. Network Simple...

We present new local search heuristics for the problem of scheduling jobs on identical parallel machines with the goal of minimizing total weighted completion time. Our proposed algorithm is a local search method based on combining a variable number of insertion moves. We develop an efficient heuristic for finding a profitable sequence of insertion moves. In a computational study, we compare th...

Variable neighborhood search (VNS) [4, 5] is a metaheuristic for solving optimization problems based on a simple principle: systematic changes of neighborhoods within the search, both in the descent to local minima and in the escape from the valleys which contain them. VNS applications have been numerous and successful. Many extensions have been made, mainly to be able to solve large problem in...

A new hybrid algorithm is proposed in this paper. An independent task scheduling algorithm is designed based on the hybrid algorithm. The hybrid algorithm adopt list scheduling method to code harmony solution and convert harmony vector to priority-based independent task scheduling model, and perform variable neighborhood search on harmony solutions to improve Harmony Search efficiency and solut...

Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS)...