In digital signal processors (DSPs) variables are accessed using k address registers. The problem of finding a memory layout, for a set of variables, that minimizes the address-computation overhead is known as the General Offset Assignment (GOA) Problem. The most common approach to this problem is to partition the set of variables into k partitions and to assign each partition to an address reg...

This article addresses a multi-stage flowshop scheduling problem with equal number of unrelated parallel machines. The objective is to minimize the makespan for a given set of jobs in the system. This problem class is NP-hard in the strong sense, so a hybrid heuristic method for sequencing and then allocating operations of jobs to machines is developed. A number of test problems are randomly ge...

A general decomposition framework for large convex optimization problems based on augmented Lagrangians is described. The approach is then applied to multistage stochastic programming problems in two di erent ways: by decomposing the problem into scenarios and by decomposing it into nodes corresponding to stages. Theoretical convergence properties of the two approaches are derived and a computa...

We propose a new rule-based pre-ordering method for Japanese-to-English statistical machine translation that employs heuristic rules in two-stages. This two-stage framework contributes to experimental results that our method outperforms conventional rule-based methods in BLEU and RIBES.

Boundedly rational heuristics for inference can be surprisingly accurate and frugal for several reasons. They can exploit environmental structures, co-opt complex capacities, and elude effortful search by exploiting information that automatically arrives on the mental stage. The fluency heuristic is a prime example of a heuristic that makes the most of an automatic by-product of retrieval from ...

University timetabling is an issue that has received more attention in the field of operations research. Course scheduling process arranging time slots and room for a class by paying to existing limitations. This problem NP-Hard problem, which means computation find solution increases exponentially with size problem. Solutions problems this kind generally use heuristic approach, tries sufficien...

This paper derives a lower bound on the average performance of a total-value greedy heuristic for the integer knapsack problem. This heuristic selects items in order of their maximum possible contribution to the solution value at each stage. We show that, as for the worst-case bound, the average performance bound for the total-value heuristic dominates the corresponding bound for the density-or...

The vehicle routing problem (VRP) is a family of problems whereby a fleet of vehicles must service the commodity demands of a set of geographically scattered customers from one or more depots, subject to a number of constraints. Early hyper-heuristic research focussed on selecting and applying a low-level heuristic at a given stage of an optimisation process. Recent trends have led to a number ...

In the present study, brain activation patterns of heuristic problem solving were investigated in the context of the puzzle Sudoku experiment by using a two-stage clustering approach. The cognitive experiment was composed of easy tasks and difficult tasks. In the two-stage clustering approach, K-means served as the data selection role in the first stage and the affinity propagation (AP) served ...