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We present a method for optimizing the layout of single tower crane and supply material locations. The crane is treated as a robot with multi degrees-of-freedom and the displacement of each joint is expressed as a cubic spline. A mathematical model is developed to generate working time optimized crane operations. Both kinematics and dynamic models are presented to describe the crane motion requirements and limitations. The constraints imposed on crane velocity, acceleration, jerk and power are considered in order to provide efficient planning and scheduling of crane operations, as well as improving the general performance and safety aspects of the crane. Solutions of the presented problem are composed of continuous and discrete variables. The continuous variables are obtained by solving the nonlinear optimization model using the NAG optimization toolbox. On the other hand, a simulated annealing algorithm is developed to obtain the discrete variables. To demonstrate the feasibility of the presented method, numerical examples have been tested and compared with other crane optimal planning methods.

In this paper, machines are allocated in horizontal rows along sides of an automated guided vehicle path so that the total cost of material transportation between machines is optimised. The problems of locating machines in single, double and multi-row layouts are addressed. Different layout arrangements as well as random permutations of machines are obtained using a simple construction algorithm, then the search for optimal solution and the best machine arrangements is obtained by implementing both Ant Colony and Simulated Annealing algorithms. Computational test examples show that the proposed method provides the best-known solutions for the single-row and double-row layout problems. Furthermore, experimental results demonstrate that both algorithms provide identical solutions for the single and multi-row layout problems.

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