Allocating energy in a first-to-n match

This paper models a decision where a player must allocate limitedenergy over a contest of uncertain length. The motivating exampleis a squash match where one of the players is not as fit asthe other. Should a player's energy be concentrated in the earlygames of the match? Should it be spread evenly over all possiblegames? Or should it be conserved for the end of the match? Wemodel this as a decision problem where, in each game, the decision-makermust determine how much energy to expend. We assume that thereare only a small number of discrete energy choices for eachgame and that the more energy the decision-maker expends, themore likely he is to win that game. We solve for the optimaldecision with dynamic programming. With only two possible energychoices for each game, we show that it does not matter how energyis expended. In the case where there are three or more energychoices, we show how to take advantage of the structure of theproblem to determine the optimal sequence of decisions. As forpractical advice, the model suggests that when the decision-makerfalls behind in a match, he ought to switch to a more conservativeapproach by dividing his remaining energy evenly among all thepossible remaining games. Received 14 May 2003. Revised 5 January 2004.     

Allocating operating funding in the public sector and the newsvendor problem

Public sector managers, particularly those at the highest level of government, tend to view lapsed (or unused) funds at the end of a fiscal year as a consequence of poor management and/or inadequate financial controls. The aim of this paper is to challenge this view. We show that the planning environment in the public sector is in essence the classical Newsvendor Problem. This simple model argues that lapsed funds are a direct consequence of a manager doing his job properly; that is, lapsed funds occur from time to time when a manager is maximizing value for the organization. An extension of the model shows that allowing low-value year-end spending has an undesirable effect on the value of spending during the year and this suggests a role for a strong audit function for year-end spending.     

The maximum return-on-investment plant location problem

The standard plant location problem determines which plants to open from a set of potential sites in order to satisfy the demands at a set of customer vertices at a minimum total cost. However, the optimal solution may exceed a limit on investment costs imposed on the enterprise in a practical setting. This paper examines the plant location problem in an environment in which the investment in plant and equipment is also an objective to be minimised. The problem is posed as a bicriterion model which examines the tradeoff between the sum of operational and investment costs and investment cost (or total cost vs sunk cost). A weighting method is used to generate efficient solutions, one of which is shown to maximise the return on investment. The integer-friendliness of the LP relaxation is investigated.     

Locating a minisum annulus: a new partial coverage distance model

The problem is to find the best location in the plane of a minisum annulus with fixed width using a partial coverage distance model. Using the concept of partial coverage distance, those demand points within the area of the annulus are served at no cost, while for ‘uncovered’ demand points there will be additional costs proportional to their distances to the annulus. The objective of the problem is to locate the annulus such that the sum of distances from the uncovered demand points to the annulus (covering area) is minimized. The distance is measured by the Euclidean norm. We discuss the case where the radius of the inner circle of the annulus is variable, and prove that at least two demand points must be on the boundary of any optimal annulus. An algorithm to solve the problem is derived based on this result.     

A Continuous Location-Allocation Problem with Zone-Dependent Fixed Cost

A zone-dependent fixed cost is introduced within the framework of minisum location of facilities in the continuous space. An efficient algorithm for determining the optimal solution for the single facility location problem is put forward, and its properties are validated. A hypothetical example is given to illustrate the algorithm. Some heuristic procedures are proposed for the multi-facility case with encouraging results.     

Locating a minisum circle in the plane

We consider the problem of locating a circle with respect to existing facilities in the plane such that the sum of weighted distances between the circle and the facilities is minimized, i.e., we approximate a set of given points by a circle regarding the sum of weighted distances. If the radius of the circle is a variable we show that there always exists an optimal circle passing through two of the existing facilities. For the case of a fixed radius we provide characterizations of optimal circles in special cases. Solution procedures are suggested.     

Location and sizing of facilities on a line

The location-allocation problem in its basic form assumes that the number of new facilities to be located is known and the capacities are unlimited. When the locations of the facilities and demand points (or customers) are restricted to the real line, the basic model may be solved efficiently by dynamic programming. In this note, we show that when the number of facilities and their capacities are included in the decision process, the problem may actually be easier to solve.     

The multi-source Weber problem with constant opening cost

A constant fixed cost of establishing a facility is introduced within the framework of minisum facility location in the continuous space. The solution method developed uses a multi-phase heuristic that first solves a discrete version of the problem by existing methods to obtain an estimate of the optimal number of facilities. Some results are presented for test problems taken from the literature and compared with best-known solutions of the multi-source Weber problem with the addition of the appropriate fixed costs.     

Local convergence in a generalized Fermat-Weber problem

In the Fermat-Weber problem, the location of a source point in ^N is sought which minimizes the sum of weighted Euclidean distances to a set of destinations. A classical iterative algorithm known as the Weiszfeld procedure is used to find the optimal location. Kuhn proves global convergence except for a denumerable set of starting points, while Katz provides local convergence results for this algorithm. In this paper, we consider a generalized version of the Fermat-Weber problem, where distances are measured by anl _p norm and the parameterp takes on a value in the closed interval [1, 2]. This permits the choice of a continuum of distance measures from rectangular (p=1) to Euclidean (p=2). An extended version of the Weiszfeld procedure is presented and local convergence results obtained for the generalized problem. Linear asymptotic convergence rates are typically observed. However, in special cases where the optimal solution occurs at a singular point of the iteration functions, this rate can vary from sublinear to quadratic. It is also shown that for sufficiently large values ofp exceeding 2, convergence of the Weiszfeld algorithm will not occur in general.