This paper aims to discuss the requirements of safe and smooth trajectory planning of transporter mobile robots to perform non-prehensile object manipulation task. In non-prehensile approach, the robot and the object must keep their grasp-less contact during manipulation task. To this end, dynamic grasp concept is employed for a box manipulation task and corresponding conditions are obtained an...

in this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (moso) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. the model was applied to solve the practical m...

the pupose of this paper is modeling of partial digest problem (pdp) as a mathematical programming problem. in this paper we present a new viewpoint of pdp. we formulate the pdp as a continuous optimization problem and develope a method to solve this problem. finally we constract a linear programming model for the problem with an additional constraint. this later model can be solved by the simp...

a new method of optimization on linear parabolic solar collectors using exergy analysis is presented. a comprehensive mathematical modeling of thermal and optical performance is simulated and geometrical and thermodynamic parameters were assumed as optimization variables. by applying a derived expression for exergy efficiency, exergy losses were generated and the optimum design and operating co...

‎In this paper we consider the minimization of a positive semidefinite quadratic form‎, ‎having a singular corresponding matrix $H$‎. ‎We state the dual formulation of the original problem and treat both problems only using the vectors $x in mathcal{N}(H)^perp$ instead of the classical approach of convex optimization techniques such as the null space method‎. ‎Given this approach and based on t...

Constraint satisfaction and combinatorial optimization form the crux of many AI problems. In constraint satisfaction, feasibility-reasoning mechanisms are used to prune the search space, while optimality-reasoning is used for combinatorial optimization. Many AI tasks related to diagnosis, trajectory tracking and planning can be formulated as hybrid problems containing both satisfaction and opti...

We present an optimization for integrity constraint veriication in distributed databases. The optimization allows a global constraint, i.e. a constraint spanning multiple databases, to be veriied by accessing data at a single database, eliminating the cost of accessing remote data. The optimization is based on an algorithm that takes as input a global constraint and data to be inserted into a l...

In this paper, we argue that partially adversarial and partially cooperative (PARC) problems in distributed arti cial intelligence can be mapped into a formalism called distributed constraint optimization problems (DCOPs), which generalize distributed constraint satisfaction problems [Yokoo, et al. 90] by introducing weak constraints (preferences). We discuss several solution criteria for DCOP ...

Constraint satisfaction problems are combinatorial optimization problems which involve finding an assignment to a set of variables that is consistent with a set of constraints. In this paper the use of two local search techniques, namely GENET and Tabu Search for constraint satisfaction optimization problems and partial constraint satisfaction problems is investigated. These methods are compare...