Search

This paper proposes efficient heuristics to solve large-scale production-distribution network design models. The problem studied is an extension of the two-echelon multicommodity CFLPSS (capacitated facility location problem with single sourcing) considering direct shipments from manufacturing facilities, alternative facility configurations, and concave inventory holding costs. After reviewing the relevant literature, a detailed description of the production-distribution network design problem studied is provided, and the problem is formulated as a mixed-integer program. The heuristic solution approach proposed is then presented. It is a variable neighborhood search (VNS) method integrating a tabu procedure. Experiments are designed to calibrate the heuristics developed, and to compare their performance with the CPLEX solver, for problems with different realistic characteristics. Computational results are presented and discussed. [ABSTRACT FROM AUTHOR]

The research leading to the modeling framework presented in this paper was motivated by the need to provide Canadian pulp and paper producers with a means of maximizing the value created from available fibre supplies. The proposed approach involves finding optimal strategies for partitioning fibre supplies into grades, allocating fibre grades to process streams, selecting appropriate production technologies and capacities, and establishing end-product range compositions and production volumes. These strategies are elaborated with a mixed-integer programming model which can be solved using commercial optimization software. Three test case scenarios are used to validate the model and illustrate how it can be applied to strategic and tactical decision making. A variant of this model has also been applied to an industrial planning problem. [ABSTRACT FROM AUTHOR]

This paper develops rolling planning horizon policies to manage material flows in multi-echelon supply — distribution networks with relatively general stochastic demand processes and procurement, transportation, inventory and shortage cost structures. Initially, the problem is formulated as a stochastic program with recourse, and its deterministic equivalent program is approximated by a multi-echelon lot-sizing model based on "risk inflated effective demands." A DRP — decomposition of this approximate model, which can be used with planning time fences or allocation algorithms, is then introduced. The use of expediting actions is also discussed. Finally, through a set of simulation experiments, the solutions obtained with our planning policies are compared with the solutions given by a classical DRP approach using safety stocks. The results show that the approach proposed leads to significant improvements. [ABSTRACT FROM AUTHOR]

The search for an appropriate balance between the supply and demand of health care services is at the centre of the nurse staffing problem in hospitals. A shortage of nursing staff results in poor service and it has a detrimental effect on the quality of care; a surplus generates unproductive costs. In this paper, a budgeting method based on a mathematical programming model is proposed to support the elaboration of a nursing budget and its allocation to hospital units. The approach takes health care system policies and labour agreements into account. The context is explained and, after discussing the existing literature and the assumptions made, a stochastic programming model of the situation is derived and an algorithm to solve it is proposed. The paper concludes by showing, with an example, how the approach can be used to arrive at well balanced budgets. [ABSTRACT FROM AUTHOR]

We consider the problem of determining optimal purchasing and shipping quantities over a finite planning horizon for arborescent, multi-echelon physical distribution systems with deterministic, time-varying demands. We assume that the inventory holding cost at a given warehouse of the distribution network is a linear function of the inventory level, and that the total procurement cost (i.e., ordering, plus purchasing, plus transportation and reception costs) is a general piecewise-linear function of the quantities shipped to and from the warehouse. We formulate a mixed integer linear programming model of the problem and develop a Lagrangian relaxation-based procedure to solve it. We show computational results for problems with 12 periods, up to 15 warehouses, and 3 transportation price ranges. [ABSTRACT FROM AUTHOR]