In this paper, an adaptive variable neighborhood search ant colony algorithm (AVNSACA) is proposed to solve the vehicle routing problem with soft time windows (VRPSTW). The algorithm’s pheromone update strategy improved make up for lack of in early stage. order avoid falling into local optimum, two operators are designed, and conditions enter set. effectiveness AVNSACA solving verified b...

This paper proposes a new two-phase hybrid metaheuristic for vehicle routing problem with time windows (VRPTW). The first phase is to minimize the number of routes by means of variable neighborhood search algorithm, while the second phase is mainly aimed at minimizing the total travel distance using tabu search algorithm. Three neighborhood search operators (All-exchange, All-2-opt, All-crossex...

This paper develops a study on different modern optimization techniques to solve the p-median problem. We analyze the behavior of a class of evolutionary algorithm (EA) known as cellular EA (cEA), and compare it against a tailored neural network model and against a canonical genetic algorithm for optimization of the p-median problem. We also compare against existing approaches including variabl...

This paper studies both the design and cyclic scheduling of multi-hoist treatment surface facilities. Former research have always assumed that production line is already available with a fixed material handling fleet size. However, in this study, number hoists considered as decision variable problem. The latter then bi-objective called Cyclic Hoist Design Scheduling Problem (CHDSP). optimizatio...

This paper proposes an effective hybrid tabu search algorithm (HTSA) to solve the flexible job-shop scheduling problem. Three minimization objectives – the maximum completion time (makespan), the total workload of machines and the workload of the critical machine are considered simultaneously. In this study, a tabu search (TS) algorithmwith an effective neighborhood structure combining two adap...

The rapid evolution of real-time multimedia applications requires Quality of Service (QoS) based multicast routing in underlying computer networks. The constrained Steiner Tree, as the underpinning mathematical structure, is a well-known NP-complete problem. In this paper we investigate a variant of variable neighborhood search, variable descent search, for the delay-constrained least-cost mult...

This paper describes JAMES, a modern object-oriented Java framework for discrete optimization using local search algorithms that exploits the generality of such metaheuristics by clearly separating search implementation and application from problem specification. A wide range of generic local searches are provided, including (stochastic) hill climbing, tabu search, variable neighbourhood search...

We present the newly developed core concept for the Multidimensional Knapsack Problem (MKP) which is an extension of the classical concept for the one-dimensional case. The core for the multidimensional problem is defined in dependence of a chosen efficiency function of the items, since no single obvious efficiency measure is available for MKP. An empirical study on the cores of widely-used ben...

A Systematic change of Neighborhood within a possibly randomized local search algorithm yields a simple and effective metaheuristic for combinatorial and global optimization. In this paper we present a Variable Neighborhood Search implementation designed to find high quality solutions for the NP-hard Linear Ordering Problem, which has a significant number of application in practice, such triang...

In this paper, we propose a Variable Neighborhood Search (VNS) algorithm based on Multi-AttributeDecision-Making (MADM) strategy under possibility environment. Further, provide numerical example to show the applicability and rationality of proposed MADM strategy.