Jack S. Cook

Multiple-type, two-dimensional bin packing problems: Applications and algorithms

In this paper we consider a class of bin selection and packing problems (BPP) in which potential bins are of various types, have two resource constraints, and the resource requirement for each object differs for each bin type. The problem is to select bins and assign the objects to bins so as to minimize the sum of bin costs while meeting the two resource constraints. This problem represents an extension of the classical two-dimensional BPP in which bins are homogeneous. Typical applications of this research include computer storage device selection with file assignment, robot selection with work station assignment, and computer processor selection with task assignment. Three solution algorithms have been developed and tested: a simple greedy heuristic, a method based onsimulated annealing (SA) and an exact algorithm based onColumn Generation with Branch and Bound (CG). An LP-based method for generating tight lower bounds was also developed (LB). Several hundred test problems based on computer storage device selection and file assignment were generated and solved. The heuristic solved problems up to 100 objects in less than a second; average solution value was within about 3% of the optimum. SA improved solutions to an average gap of less than 1% but a significant increase in computing time. LB produced average lower bounds within 3% of optimum within a few seconds. CG is practical for small to moderately-sized problems — possibly as many as 50 objects.

Achieving Competitive Advantages of Advanced Manufacturing Technology

Change is an essential business trait. Manufacturing particularly is transforming at an unprecedented pace. Adopting effective management practices, capable of keeping pace with the changing technological environment, is particularly important to success in global markets. Manufacturers employing advanced manufacturing technology (AMT) are often more flexible than their traditional counter‐parts since AMT permits the integration of product design and production processes. Consequently, this synergistic effect facilitates achievement of world‐class manufacturing objectives. Despite obvious advantages, sparse research exists concerning achieving AMT competitive advantages. To incorporate AMT organizationally, management must be cognizant of the requirements for successful AMT implementation. Provides managerial requirements for successfully achieving AMT competitive advantages. Assuming management understands the “how” of doing things right and incorporates the necessary corporate cultural changes to embrac...

Optimal robot selection and workstation assignment for a CIM system

In this paper, a mathematical program and solution algorithm is developed for optimal robot selection and workstation assignment for a CIM system. In specific, our model considers selection of a proper mix of multiple-type robots such that operational requirements from a given number of work- stations are satisfied at minimal system cost. Each robot is characterized by its fixed charge, and subject to limits on machine time and work envelope. Each workstation has known demands on both robot machine time and work space. The model is formulated as a pure 0-1 mathematical program and is shown harder than two-dimensional bin packing, a well-known NP-hard problem. A three-phase optimization algorithm is implemented and tested by solving 450 randomly generated problems. Computational results indicate the solution algorithm is effective in solving problems of a practical size (i.e., 50 workstations and a maximum of 20 robots) within acceptable computational times. >