An overview of some methods of statistical physics applied to the analysis of algorithms for optimization problems (satisfiability of Boolean constraints, vertex cover of graphs, decoding, ...) with distributions of random inputs is proposed. Two types of algorithms are analyzed: complete procedures with backtracking (Davis-Putnam-Loveland-Logeman algorithm) and incomplete, local search procedu...

A new evolutionary algorithm, Backtracking Search Algorithm (BSA), is applied to solve constrained optimization problems. Three constraint handling methods are combined with BSA for constrained optimization problems; namely feasibility and dominance (FAD) rules, e-constrained method with fixed control way of e value and a proposed e-constrained method with self-adaptive control way of e value. ...

differential steering of in-wheel electric vehicle provides the functions of both active steering and power assisted steering with the coupling control of force and displacement transfer characteristic of system. a collaborative optimization model of the differential power-assisted steering system of in-wheel electric vehicle is built, with steering economy as the main system optimization goal,...

This study introduces an effective population-based optimization algorithm, namely the Golden Search Optimization Algorithm (GSO), for numerical function optimization. The new algorithm has a simple but strategy solving complex problems. GSO starts with random possible solutions called objects, which interact each other based on mathematical model to reach global optimum. To provide fine balanc...

one of the most important extensions of the capacitated vehicle routing problem (cvrp) is the vehicle routing problem with simultaneous pickup and delivery (vrpspd) where customers require simultaneous delivery and pick-up service. in this paper, we propose an effective ant colony optimization (eaco) which includes insert, swap and 2-opt moves for solving vrpspd that is different with common an...

the synthesis of heat integrated multi-component distillation systems is complex due to its huge search space for structural combination and optimization computation. to provide a systematic approach and tools for the synthesis design of distillation systems, a new method for modeling heat integrated columns is presented, and the operating cost objective function is minimized by improved harmon...

Heuristics are crucial tools in decreasing search effort in varied fields of AI. In order to be effective, a heuristic must be efficient to compute, as well as provide useful information to the search algorithm. However, some well-known heuristics which do well in reducing backtracking are so heavy that the gain of deploying them in a search algorithm might be outweighed by their overhead. We p...

There are three main algorithmic techniques for solving constraint satisfaction problems: backtracking search, local search, and dynamic programming. In this chapter, I survey backtracking search algorithms. Algorithms based on dynamic programming [15]— sometimes referred to in the literature as variable elimination, synthesis, or inference algorithms—are the topic of Chapter 7. Local or stocha...

gravitational search algorithm (gsa) is one of the newest swarm based optimization algorithms, which has been inspired by the newtonian laws of gravity and motion. gsa has empirically shown to be an efficient and robust stochastic search algorithm. since introducing gsa a convergence analysis of this algorithm has not yet been developed. this paper introduces the first attempt to a formal conve...

The fluence map optimization (FMO) problem is a core problem in intensity modulated radiation therapy (IMRT) treatment planning. Although it has been studied extensively for site-specific treatment planning, few studies have examined efficient computational methods for solving it for intensity modulated total marrow irradiation (IM-TMI) planning; few studies have also looked at exploiting prior...