Abstract: A method and system for integrating job shop scheduling with discrete event simulation for manufacturing facilities are provided. In one aspect a simulator simulates discrete events of a facility using a job schedule generated by a scheduler. The simulator simulates the facility based on one or more local rules, one or more resources, and one or more parameters associated with said locals rules and said resources. The simulator further models said one or more parameters as random variables and using said random variables in its simulation of the facility. The scheduler receives feedback based on output from the simulating step. The feedback includes at least an instruction to the scheduler to include at least one of said one or more resource and to change said one or more parameters based on said modeling of said one or more parameters as random variables. The scheduler uses the feedback for generating an updated schedule.

Abstract: Automated mapping of part numbers associated with parts in a bill of materials (BOM) submitted by a BOM originator to internal part numbers assigned to those parts by a BOM receiver is performed by one or more computers connected to one or more networks through one or more network interfaces. A first receive component receives one or more data sets containing historical data on bills of materials received in the past by the BOM receiver. A second receive component receives one or more data sets containing known mappings between internal part numbers used by the BOM receiver, and part numbers used by various BOM originators. A third receive component receives one or more data sets containing information of various parameters and their values describing the parts to which the BOM receiver has assigned internal part numbers.

Abstract: A method of scheduling of the manufacturing operations required to produce cast steel products from molten iron in a steel manufacturing plant.

Abstract: An automated method optimally designs plates to satisfy an order book at a steel plant so as to maximize the yield of the plates designed while using capacity fully to reduce the production of surplus slabs or plates, and satisfy order deadlines. Our method consists of four main components: (1) mother plate design, (2) slab design, (3) cast design, and (4) material allocation. A column generation framework for mother plate design is used where the problem is decomposed into a master problem and a subproblem. The master problem is used to evaluate packing patterns that should be used to fulfill the order book and the subproblem generates potential one-dimensional and two-dimensional feasible packing patterns as candidates to be evaluated by the master problem. The solution to the master problem produces a list of mother plates that need to be produced. These mother plates are transformed into candidate slabs, which are represented via an interval graph.

Abstract: A computer system provides one or more lists of product combinations to one or more shoppers over one or more networks. The computer system comprises one or more central processing units (CPUs), one or more memories, and one or more network interfaces to one or more networks. An electronic shopping assistant process implemented on the computer system receives one or more inputs of constraints from shoppers, sends out the inputs to one or more shopping list generating processes in one or more stores, receives one or more lists of recommended product combinations that satisfy the given constraints, and allows shoppers to view and select one or more product combinations from received lists.

Abstract: A computer system and method uses one or more virtual wish lists of one or more shoppers over a computer network. One process extracts information from online address books or other personal databases, and creates lists of recipients for whom a shopper wants to purchase products. A second process obtains virtual wish lists of recipients by observing their visits to online stores, and other online behavior. Recipients are asked for permission to make this data available to other shoppers, online stores, and other Web sites. Recipients can modify their virtual wish lists, and selectively approve of their use by other shoppers, etc. A third process creates shopping lists for the recipients, and generates lists of recommended products for shoppers to buy for intended recipients.

Abstract: A method is provided for identifying a cost-minimizing bid set in a reverse combinatorial auction subject to various business rules for all-or-nothing bundled bids. The method includes introducing a decision variable for each bid, introducing a counting variable to indicate whether bids from a supplier are chosen in an optimal bid set, modeling demand constraints for each item using the bid variables, modeling minimum and maximum numbers of suppliers based on the counting variables, introducing dummy variables to ensure existence of feasible solutions, for a given cost formulating an objective of choosing bids that arrive early based on an additional timestamped objective with the given cost level as a constraint, and introducing price modifications to handle the formulated objective of choosing bids that arrive early.

Abstract: Disclosed is a method for computing payment discounts awarded to winning agents in an exchange, said method comprising computing a Vickrey discount to each said winning agent as the difference between available surplus with all agents present minus available surplus without said winning agent, and computing said payment discounts by adjusting said Vickrey discounts so as to constrain said exchange to budget-balance.

Abstract: An efficient computer implemented method is used to design slabs for production from an order book. This method minimizes the number of slabs designed to fulfill an order book. This method is based on a heuristic algorithm which is a variant of the greedy approach for the set covering method. The variations are novel in three ways. First, designing slabs using the flexibility in the order size; second, using weight for choosing large slabs; and third, controlling the exponential nature of enumeration of the set of all subsets by constructing only the largest slab at each step.

Abstract: A fast computer implemented method generates near-optimal solutions to the multi-objective inventory matching problem by solving for multiple objectives simultaneously and generating multiple non-dominating solutions. The method implements a multi-assignment backjumping algorithm that consists of three steps. The first step is a rappeling step in which a feasible solution is created by applying Iterative Bipartite Matching and maximum flow algorithm. Near-optimal feasible solutions are stored in a non dominated set. The second step is to use a multi-key sort to identify undesirable matches in a given feasible solution. The third step is backlifting the solution by removing undesirable matches from the feasible solution and places those undesirable matches on a no good set of matches. If the feasible solution is non-dominated, a copy is stored in a non-dominated set. The feasible solution is finally provided as input to the repelling step.