Currently, the research of emergency supplies distribution and decision models mostly focus on deterministic models and exact algorithm. A few of studies have been done on the multi-level distribution network and matheuristic algorithm. In this paper, random processes theory is adopted to establish emergency supplies distribution and decision model for multi-level network. By analyzing the char...

The n-dimensional direct search algorithm DIRECT of Jones, Perttunen, and Stuckman has attracted recent attention from the multidisciplinary design optimization community. Since DIRECT only requires function values (or ranking) and balances global exploration with local refinement better than n-dimensional bisection, it is well suited to the noisy function values typical of realistic simulation...

Sparse unmixing (SU) can represent an observed image using pure spectral signatures and corresponding fractional abundance from a large library is important technique in hyperspectral unmixing. However, the existing SU algorithms mainly exploit spatial information fixed neighborhood system, which not sufficient. To solve this problem, we propose nonlocal weighted algorithm based on global searc...

the cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. to enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. normally, the parametersof the cuckoo search are kept constant. this may lead todecreasing the efficiency of the algorithm. to cop...

one of the mostly used enhanced oil recovery methods is the injection of water or gas under pressure to maintain or reverse the declining pressure in a reservoir. several parameters should be optimized in a fluid injection process. the usual optimizing methods evaluate several scenarios to find the best solution. since it is required to run the reservoir simulator hundreds of times, the process...

In this paper, we review parallel search techniques for approximating the global optimal solution of combinatorial optimization problems. Recent developments on parallel implementation of genetic algorithms, simulated annealing, tabu search, and greedy randomized adaptive search procedures (GRASP) are discussed.

A random search algorithm intended to solve discrete optimization problems is considered. We outline the main components of the algorithm, and then describe it in more detail. We show how the algorithm can be implemented on parallel computer systems. A performance analysis of both serial and parallel versions of the algorithm is given, and related results of solving test problems are discussed....

This paper considers the scheduling problem of parallel batch processing machines with non-identical job size and processing time. In this paper, a new mathematical model with ready time and batch size constraints is presented to formulate the problem mathematically, in which simultaneous reduction of the makespan and earliness-tardiness is the objective function. In recent years, the nature-in...

This paper presents a new evolutionary method for solving the satisfiability problem. It is based on a parallel cellular genetic algorithm which performs global search on a random initial population of individuals and local selective generation of new strings according to new defined genetic operators. The algorithm adopts a diffusion model of information among chromosomes by realizing a two-di...