Mean-Life Indifference Pricing for Quantity Purchases

Traditionally, consumers pay a fixed price for a quantity of items based on a presumed mean life. In many cases (i.e., federal government procurement) a sample of items is pretested to determine mean life and hence conformance to the contract. This paper suggests an alternative scheme based on a price indifference curve h(φ) which specifies the unit cost given mean life φ, which is estimated based on the actual performance of the first r items that fail. The paper develops a specific form for the indifference function and a procedure for estimating both φ and h(φ) and presents an example.     

Renewal approximations for the departure processes of batch systems

In this paper we consider three standard batch arrival/service systems and develop renewal process approximations for the inter-departure time squared coefficient of variations. The systems considered are: (i) batch arrival with individual service; (ii) batching for setup reduction for a single server system; and (iii) batch processing. The random version of the batch arrival with individual service case naturally results from random branching of individuals following a batch service process. This case is also developed with the intent of improving the modeling results for downstream workstations following a batch service process.     

Incentive Contracting Based Upon Consumer Indifference

In contract purchasing, price is often negotiated, given a reliability specification. Prior to procurement a sample is taken to determine if the product meets the reliability specification. This paper considers an alternative approach in which the contract price reflects actual field performance for an item subject to two types of failures. A consumer indifference curve that specifies the predicted break-even point between price and reliability is used to establish the initial purchase price. The actual purchase price is determined by estimating the break-even point based upon a sample of failures. Both the vendor and consumer agree upon the statistical methods for revising the price at purchase time. In this manner, more reliable products yield higher prices than less reliable products, thus resulting in a quantifiable incentive contract.     

cdf/BOSS: A language and microcomputer implementation for discrete simulation

A discrete simulation modeling language and microcomputer environment is described. The language extends the well-known block orientation to a full structured programming language. The language was specifically designed to support the needs of education and this is accomplished by the self-contained environment, and the syntax and capabilities of the language. Real-time animation and user interrupt capabilities enhance the learning process as well as the modeling and analysis process.     

Deadlock detection and resolution for discrete-event simulation: multiple-unit seizes

This paper develops an automatic scheme to detect and resolve deadlocks in discrete-event simulation systems with entities capable of requesting multiple units of a resource. The research extends earlier deadlock work on discrete simulation systems with unit resource requests. The purpose of the deadlock handling scheme is to provide for additional capabilities in discrete simulation systems. This is accomplished by endowing the simulation system with appropriate data structures and algorithms. The algorithms presented are based on a graph model of deadlocks in the simulation system. The proposed algorithms identify different categories of permanent and transient deadlocks in the simulation system. A deadlock resolution scheme is also developed in the case of group-processing for permanent deadlocks.     

Optimal Scheduling of Multiple Feedstock Batch Biogas Production Systems

Biomass to methane production systems have the potential of supplying 25% of the yearly national natural gas demand. The production systems associated with this conversion process are anaerobic digestion facilities. The optimal operation of a batch biomass digester system requires the scheduling of all batches from multiple feedstocks during a fixed time horizon. A significant characteristic of these systems is that the feedstock decays in storage before use in the digester system. The optimal batch residence times in the digester must account for the production rate as well as the decay rate of stored biomass. The availability times, biomass quantities, biogas production rates and storage decay rates must all be taken into account for maximal biogas production to be achieved during the planning horizon. This paper addresses the scheduling of both single and multiple feedstocks in a single digester system. The single feedstock batch scheduling time problem is solved by a dynamic programming algorithm. The multiple feedstock problem is solved by a decomposition approach where the master level allocates time to each feedstock while the subproblems schedule batches within these time allocations.     

A New Approach for Network Reliability Analysis

This paper presents a novel approach to network reliability analysis based on a network function. Once this function has been calculated for a given system, the network is no longer needed in the analysis. The approach is far more efficient than Monte Carlo simulation and much more flexible than cut-set techniques.