There are several approaches for solving hard optimization problems. Mathematical programming techniques such as (integer) linear programming-based methods and metaheuristic two extremely effective streams combinatorial Different research streams, more or less in isolation from one another, created these two. Only years ago, many scholars noticed the advantages enormous potential of building hy...

In this paper we prove that in some practical situations, there is a free lunch for hyper-heuristics, i.e., search algorithms that search the space of solvers, searchers, meta-heuristics and heuristics for problems.

Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing or generate new ones, holds high relevance this matter. Current research suggests that, under certain circumstances, hyper-heuristics outperform single heuristics when evaluated isolation. When are selected algorithms, th...

We present dual heuristics for the directed cut formulation of the Steiner problem in graphs. These heuristics usually give tight lower and upper bounds, and are enough to quickly solve two thirds of the instances from the literature. For harder instances, we propose two exact algorithms using those heuristics: branch-and-ascent, an implicit enumeration without LP solving; and a branch-and-cut ...

Latency reduction in distributed interactive applications has been studied intensively. Such applications may have stringent latency requirements and dynamic user groups. We focus on application-layer multicast with a centralized approach to the group management. The groups are organized in overlay networks that are created using graph algorithms that create a tree structure for the group. A tr...

Message scheduling is shown to be very effective in belief propagation (BP) algorithms. However, most existing scheduling algorithms use fixed heuristics regardless of the structure of the graphs or properties of the distribution. On the other hand, designing different scheduling heuristics for all graph structures are not feasible. In this paper, we propose a reinforcement learning based messa...

We consider a version of pattern matching useful in processing large musical data: matching, which consists in finding matches which are -approximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance between two symbols , is measured as . We also consider -matching, where is a bound on the total sum of the diff...

This study aims to discuss the solution methodology for a closed-loop supply chain (CLSC) network that includes the collection of used products as well as distribution of the new products. This supply chain is presented on behalf of the problems that can be solved by the proposed meta-heuristic algorithms. A mathematical model is designed for a CLSC that involves three objective functions of ma...

One-dimensional decompositionof nonuniformworkload arrays for optimal load balancing is investigated. The problemhas been studied in the literature as "chains-on-chains partitioning" problem. Despite extensive research efforts, heuristics are still used in parallel computing community with the "hope" of good decompositions and the "myth" of exact algorithms being hard to implement and not runti...

The constraint satisfaction community has developed a number of heuristics for variable ordering during backtracking search. For example, in conjunction with algorithms which check forwards, the Fail-First (FF) and Brelaz (Bz) heuristics are cheap to evaluate and are generally considered to be very eeective. Recent work to understand phase transitions in NP-complete problem classes enables us t...