Dan B. Rinks

Interactive solutions for the linear multiobjective transportation problem

Abstract Mathematical programming problems that exhibit the mathematical structure of a transportation problem often arise in settings with multiple conflicting objectives. Existing procedures for analyzing these problems fall into two general categories. These methods either generate all nondominated solutions or they construct a single compromise solution. This paper presents two interactive algorithms which take advantage of the special form of the multiple objective transportation problem. Two examples are included to illustrate these algorithms and to demonstrate their viability.

Critical path in an activity network with time constraints

Abstract An acyclic graph with nonnegative weights and with a unique source and destination is called an activity network. A project comprised of a set of activities and precedence relationships can be represented by an activity network and the mathematical analysis of the network can provide useful information for managing the project. In a traditional activity network, it is assumed that an activity can begin any time after all of its preceding activities have been completed. This assumption does not adequately describe many practical situations, in which some kinds of time constraint are usually associated with an activity. In this paper, we investigate two types of time constraint commonly encountered in project management. The first is the time-window constraint , which assumes that an activity can begin its execution only in a specified time interval. The second is the time-schedule constraint , which requires that an activity begin only at one of pre-specified beginning times. An efficient, linear time algorithm for finding the longest path (critical path) and for analyzing the flow time of each arc is developed for activity networks with these time constraints.

Three Types of Producer's and Consumer's Risks in the Single Sampling Plan

The classical producers risk and the classical consumers risk are defined in acceptance sampling based on the assumption that the proportion defective of incoming lots is a constant. This assumption has been a focus of much of the criticism of accepta..

Optimal policy surfaces for a multi-item inventory problem

Abstract A multi-item inventory problem under periodic review with unspecified single-item ordering and storage costs is considered in this paper. The problem as posed involves multiple aggregate objectives and constraints. An approximate solution methodology is derived based on asymptotic properties from renewal theory. The results are presented in the form of an optimal policy surface that shows the tradeoff of the cost of a policy versus customer service, while satisfying the workload for handling orders and storage room space constraints.

Empirical study of a new procedure for allocating safety stock in a wholesale inventory system

Abstract A periodic review, single-item control model for a wholesale system that consists of one warehouse and N stores is considered. Schneider, Rinks and Kelle have developed a methodology that yields approximately optimal ( s , S ) policies for managing such an inventory environment as a coordinated system. In this paper an exntensive empirical study to test the approximations of the Schneider et al. model is presented. The focus of the paper is on developing general guidelines concerning the effect that system parameters have on the optimal service level at the warehouse.

Rationing safety stock in the USAF's multi echelon inventory system

Abstract The United States Air Force (USAF) operates one of the largest multi-echelon inventory systems in the world. Individual bases hold inventory to meet the demands of their customers at the base. These bases are re-supplied by central depots that are, in turn, re-supplied by vendors. The Air Force Logistics Command (AFLC) has proposed the adoption of a method of rationing assets at the depot as a means of improving weapon system availabilities. A large scale simulation model of the USAFs multi-echelon inventory system was used to study the effects of such a rationing procedure. The simulation results demonstrate that the consequences of the proposed rationing scheme are contrary to what had been intuitively expected. In fact, the proposed policy change would have decreased rather than increased performance.

REVENUE ALLOCATION METHODS FOR INTEGRATED TRANSIT SYSTEMS

Abstract Revenue allocation in the context of an integrated transit system involves the splitting of joint revenues derived from passengers taking system trips, that is, trips that involve a transfer between properties of two or more of the participants in an integrated system. The general nature of the revenue allocation problem is first reviewed. Next, a framework for constructing and assessing revenue allocation models is developed. A macroprocess model is described; categories of variables that merit consideration for inclusion in revenue/cost allocation formulas are discussed; and criteria for evaluation of models are examined. After doing this, five general approaches to the problem of allocating joint revenues are discussed and evaluated. Finally, a general revenue-sharing model based on ridership is developed. The model is then used to examine several relevant issues in pricing system trips and fare collection.

Maintenance project management in the process industries: A look at the realities

Abstract Realistic issues regarding maintenance project management in the process industries are examined. Guidelines and examples are provided under well-accepted project management headings and presented with a focus on the need for timely, meaningful information.

A multivariate utility function approach to stochastic capacity planning

Abstract The problem being considered is the expansion of a single capacity when the installation cost is large and there are neither absolescence nor spatial effects on the expansion. Demand is assumed to follow an evolving process; in particular, the demand increments are normally distributed with linearly increasing mean and variance in time (i.e., a Wiener process). Selecting the optimum size and timing of capacity additions in the face of uncertain demand forecasts involves both the minimization of cost as well as the minimization of risk. For the situation where demand acts as a Wiener process, Kang and Park have derived the expectation of the “equivalent cost rate.” Using the standard deviation of the equivalent cost rate as a measure of the risk of expansion, Kang and Park then minimized an objective function that was a linear combination of cost and risk. The purpose of this paper is to extend this line of research. Using standard decision analysis procedures, a multiattribute utility function is constructed that reflects the decision makers trade-off for cost and risk. A significant advantage of the utility function approach is that it allows for nonlinear trade-offs of cost and risk.

A process model of fare decision making for integrated transit systems

Abstract Based on interviews with transit officials in several American cities, a process model for evaluating proposals to integrate local transit properties into an area-wide transportation system is developed. Relevant factors for a data base are discussed and the information processing flows are described. In this model, negotiation between the participants plays an important role in constructing and assessing revenue allocation plans.