Eldon A. Gunn

Forest management challenges for operational researchers

This is an overview of operational research work that has been carried out to support strategic forest management planning, short term forest planning, forest operations, and forest fire management. It identifies important unresolved problems and new challenges that could serve as a rich source of problems for both practitioners and researchers.

A review of warehouse models

Abstract Literature aimed at optimizing the throughput capacity, storage and design of warehouses is reviewed. Throughput capacity models are comprised of picking policies, batching policies, storage assignment policies, as well as dynamic control models. Storage capacity models either find the optimal warehouse size or else maximize space utilization. Finally, questions such as rack orientation, space allocation and external building configuration are the focus of warehouse design models.

Operations Research challenges in forestry: 33 open problems

Forestry has contributed many problems to the Operations Research (OR) community. At the same time, OR has developed many models and solution methods for use in forestry. In this article, we describe the current status of research on the application of OR methods to forestry and a number of research challenges or open questions that we believe will be of interest to both researchers and practitioners. The areas covered include strategic, tactical and operational planning, fire management, conservation and the use of OR to address environmental concerns. The paper also considers more general methodological areas that are important to forestry including uncertainty, multiple objectives and hierarchical planning.

On coordinating warehouse sizing, leasing and inventory policy

Abstract Organizations often fulfil their storage needs by supplementing their own warehouse with leased space, a scenario modeled here under the assumption of constant product demand. Closed-form formulae are obtained for the decision variables of interest, namely, the replenishment lot size and the warehouse size, as well as the amount of space to lease. Cost savings due to leasing are shown to have an upper bound of approximately 29% when the optimal warehouse capacity can be installed without restrictions (such as a budgetary constraint). A numerical example further indicates that leasing is significantly more beneficial when the warehouse size is tightly constrained, and that total costs are robust with respect to demand fluctuations.

Some Perspectives on Strategic Forest Management Models and the Forest Products Supply Chain

Abstract The modeling approach used by most organizations to do strategic wood supply analysis usually pays little attention to the location issues that are important to the supply chain. This paper raises questions about the conventional approach and suggests that the strategic linear programming models should contain much more spatial and market information. We point out that there is much more flexibility in sustainable harvests in terms of forest types than is usually recognized. It is possible to exploit this flexibility to gain more flexibility in coordinating spatial harvests with both ecological and supply chain requirements.

A simple SLP algorithm for solving a class of nonlinear programs

Successive linear programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. We present an approach for a special class of nonlinear programming problems, which arise in multiperiod coal blending. The class of nonlinear programming problems and the solution approach considered in this paper are quite different from previous work. The algorithm is very simple, easy to apply and can be applied to as large a problem as the linear programming code can handle. The quality of solution, produced by the proposed algorithm, is discussed and the results of some test problems, in the real world environment, are provided.

Planning harvesting and marketing activities for integrated fishing firms under an enterprise allocation scheme

Abstract This paper focuses on the tactical planning problem for integrated fishing enterprises operating in Canadas Atlantic Groundfish industry. A firm with a fleet of trawlers, a number of processing plants, quasi-property rights to fish in the sea, and market requirements, must coordinate harvesting and marketing strategies which will allow it to maximize potential revenue. To achieve this, we outline a large-scale linear programming model which maximizes net revenue from product sales less fleet operating costs, subject to marketing and fleet operating constraints. The output of the multi-period linear program suggest what products and their respective volumes should be marketed, and how raw fish should be caught in order to satisfy marketing requirements. We demonstrate the planning and diagnostic potential of the linear program by solving an example problem based on data obtained from a large Atlantic seafood company.

Dispatching a fishing trawler fleet in the Canadian Atlantic groundfish industry

Abstract An integrated fish-processing firm in the Canadian Atlantic demersal fishery usually owns a fleet of fishing trawlers. For a given planning horizon, the firm must find a minimum-cost fleet dispatching plan in order to satisfy demands for various species at its processing plants. In this paper, we formulate two cases of this trawler dispatch problem as mixed-integer programming models. In addition, we develop heuristics for solving both problems. Results for several sample problems, show quite favorable performance by the heuristic methods. Solution quality averaged within 2% of Lagrangean lower bounds. Also, using three test problems extracted from a firms historical fishing records, we produce in a deterministic setting, solutions which represent up to 30% improvement over the firms real-time solutions.

A Decomposition Method Based on the Augmented Lagrangian

AbstractIn this paper, we explore the use of the augmented Lagrangian in a decomposition method which is a direct application of the “method of multipliers”. Contrary to popular opinion, the use of the augmented Lagrangian does not necessarily destroy separability inherent in a problem. This separability can be recovered by the use of sequential linearization algorithms, of which the Frank-Wolfe algorithm is an example. We outline this decomposition approach in a fairly general framework and then specialize it to the decomposition of linear programs. Linear programs are, in at least one sense, the worst case for a method of multipliers approach since little is known about the rate of convergence of the dual multipliers in tMs case. We report some computational evidence from two linear programming problems related to forest management which indicates that empirical convergence rates can be quite satisfactory.

Queues with switchover - A review and critique

In many important applications, a situation is encountered where the service capacity of a server must be switched between various competing classes of customers. In most situations, this switchover is not costless. A penalty must be paid either in terms of lost service capacity during the switching period or in terms of a cost to carry out the switching or both. Although queues with switchover abound in applications, generally applicable results are not widely available. In this paper, we review and analyze optimal control policies for queues with switchover. We point out that ideas from several diverse areas can be applied to these models.