Real-time search methods allow an agent to perform pathfinding tasks in unknown environments. Some of these methods may plan several actions per planning step. We present a novel approach, where the number of planned actions per step depends on the quality of the heuristic values found in the lookahead. If, after inspecting the neighborhood of a state, its heuristic value changes, only one acti...

The driver scheduling problem at Chinese electric multiple-unit train depots becomes more and difficult in practice is studied very little research. This paper focuses on defining, modeling, solving the depot which can determine size schedule simultaneously. To solve this problem, we first construct a time-space network based formulate as minimum-cost multi-commodity flow problem. We then devel...

This study’s purpose is to explain the development of Blue Bird taxi company as provider mass transportation service in Indonesia between years 1970-2015. The research method used this history method, which consists heuristic, verification, interpretation, and historiography. In heuristic phase, researcher gathered resources from primary sources such a book titled Sang Burung Biru, well newspap...

Using the formalism of rigorous statistical mechanics, we study the phenomena of phase separation and freezing-point depression upon freezing of solutions. Specifically, we devise an Ising-based model of a solvent–solute system and show that, in the ensemble with a fixed amount of solute, a macroscopic phase separation occurs in an interval of values of the chemical potential of the solvent. Th...

university course timetabling is a complex optimizationproblem. there are many components like departments, faculties, rooms,and students making the problem huge and difficult to solve. eachcomponent enforces a set of normally conflicting constraints on thesolution space. the problem will be solved if courses are scheduled indifferent rooms and within some specific time slots such that a set of...

In this paper we present two hyper-heuristics developed for the Cross-Domain Heuristic Search Challenge. Hyper-heuristics solve hard combinatorial problems by guiding low level heuristics, rather than by manipulating problem solutions directly. Two hyper-heuristics are presented: Five Phase Approach and Genetic Hive. Development paths of the algorithms and testing methods are outlined. Performa...

Data decomposition across processors is critical to the performance of data parallel programs on distributed-memory machines. The data decomposition problem involves data alignment and data distribution. This paper addresses the data alignment phase which can be classiied into slope alignment and ooset alignment. We propose a data reference graph (DRG) model. Based on the DRG model, a slope ali...

We introduce a new genetic algorithm (GA) approach for the integrated inventory distribution problem (IIDP). We present the developed genetic representation and use a randomized version of a previously developed construction heuristic to generate the initial random population. We design suitable crossover and mutation operators for the GA improvement phase. The comparison of results shows the s...

We introduce a parameter that measures the “constrainedness” of an ensemble of combinatorial problems. If problems are over-constrained, they are likely to be insoluble. If problems are under-constrained, they are likely to be soluble. This constrainedness parameter generalizes a number of parameters previously used in different NP-complete problem classes. Phase transitions in different NP cla...

We introduce a parameter that measures the \con-strainedness" of an ensemble of combinatorial problems. If problems are over-constrained, they are likely to be insoluble. If problems are under-constrained, they are likely to be soluble. This constrainedness parameter generalizes a number of parameters previously used in diierent NP-complete problem classes. Phase transitions in diierent NP clas...