Umit Akinc

In the face of growing competition, the Western manufacturing management is forced into becoming much more frugal in resource management. Just-in-time (JIT) is a set of principles which, by attacking all types of waste in manufacturing, can help management to achieve ...

ABSTRACT This paper presents an efficient algorithm for the general (as opposed to the binary) knapsack problem. The algorithm generates tight bounds on the variables from the LP relaxation of the problem which give the optimal values of most of the variables very quickly. A branch-and-bound procedure is then employed to solve the remaining reduced problem. Extensive computatonal tests have confirmed the efficiency of this approach for a wide variety of problems with as many as 5000 variables.

ABSTRACT In the “make-to-forecast” production environment, competitive market dynamics require customer delivery times substantially shorter than the fixed manufacturing lead times, which require the release of units into production without prior knowledge of customers' desires. As a result, there is the possibility of either getting more orders than can be accommodated causing the rejection of some, or getting too few orders leading to a finished unit without a buyer, which we term an “orphan”. The physical size and dollar value of the units make storing of the orphans, if not completely impossible in some situations, at least extremely undesirable. The likelihood of these two undesirable events depends on the managerially predetermined production capacity relative to the exogenous average order arrival rate. If the capacity is excessive, too many units will be orphaned, whereas insufficient capacity will result in too many rejected orders. We present a Markov model to analyze the behavior of the system in regard to orphan and order rejection levels. The analysis provides management and researchers with highly generalizable insights into managing this common dilemma under various demand and policy scenarios to make more informed capacity level decisions.

Abstract This paper proposes a new framework for modelling aggregate production planning problems in which emphasis is placed upon offering the user the flexibility to specify (1) the production options to be employed, (2) the relationships among those options (some of which may be highly situation-specific), and (3) the relevant cost structure. The procedure offered for solving the problem embeds Bowmann's “transportation” approach to aggregate production planning into a large mixed integer programming framework.

Estuda-se a programação de preparações de máquinas e atividades produtivas de uma indústria têxtil, localizada na Carolina do Norte, EUA. A firma enfrenta o problema de programar a produção das encomendas dos clientes em diversos teares circulares, que admitem diferentes configurações, mediante instalação de diferentes cilindros, para tecer vários tipos de malha crua. Dado um conjunto de requisitos, para diferentes estilos de malha, o problema consiste em decidir quanto à configuração específica a ser usada em cada máquina e quanto aos específicos pedidos a serem processados nessas configurações. O problema é formulado como um modelo de programação linear inteira. O objetivo é a maximização da contribuição total de todos os pedidos programados sujeitos a restrições impostas à capacidade de produção pelas máquinas e pelas operações de preparação, considerando explicitamente os efeitos dos ajustes programados e das restrições ao atendimento das encomendas dos clientes. São discutidas ...

The subject of this paper is the formulation and solution of a variation of the classical binary knapsack problem. The variation that is addressed is termed the “fixed-charge knapsack problem”, in which sub-sets of variables (activities) are associated with fixed costs. These costs may represent certain set-ups and/or preparations required for the associated sub-set of activities to be scheduled. Several

ABSTRACT We address the situation of a firm that needs to dispose of a large, expensive asset (e.g., car, machine tool, earth mover, turbine, house, airplane), with or without a given deadline (and either known or unknown to the buyer). If a deadline exists, the asset is salvaged at a known value which may be zero, or even negative if there is a disposal cost. The asset has a known holding cost and may also have an initial nominal (undiscounted) price. The question is how, if at all, the price should be discounted as time progresses to maximize the expected proceeds. We use a dynamic recursion where each decision stage can be optimized based on classic economic monopoly pricing theory with a demand intensity function estimated from sales data, and show that the model is well‐behaved in the sense that the optimal price and optimal expected revenue monotonically decline as the deadline approaches. We test the model by comparing its optimal price pattern to the official pricing policy practiced at a used‐car dealer. We then extend the model to situations where the buyer knows the seller's deadline and thus may alter his behavior as the deadline approaches.

This paper deals with the problem of delivering a well-defined service to a given set of points efficiently. Efficiencies are sought through providing the services by use of a mobile service unit (MSU). The service facility is mobile in the sense that it can move from point to point at ...

In blending problems there are typically specification constraints that limit the content of various properties of the blend that it acquires from the ingredients to certain maximum or minimum percentages of the total blend. For sake of linearity, these constraints are commonly included in the problem in a way that precludes direct sensitivity analysis with respect to changes in these percentages. This note shows that the sensitivity analysis with respect to changes in the target specification percentages can be derived from the ordinary sensitivity analysis with minimum additional effort; and that common LP codes can be slightly modified to facilitate sensitivity analysis of blending percentages.

In blending problems there are typically specification constraints that limit the content of various properties of the blend that it acquires from the ingredients to certain maximum or minimum percentages of the total blend. For sake of linearity, these constraints are commonly included in the problem in a way that precludes direct sensitivity analysis with respect to changes in these percentages. This note shows that the sensitivity analysis with respect to changes in the target specification percentages can be derived from the ordinary sensitivity analysis with minimum additional effort; and that common LP codes can be slightly modified to facilitate sensitivity analysis of blending percentages.

The make-to-forecast manufacturing environment is characterized by the manufacture of individual, expensive-to-store units which come in alternative configurations or models. Since the production lead times are longer than customers are willing to wait, production is started in anticipation of orders for particular models and then modified while in production, if economically desirable, to match the actual customer orders. Ideally, no finished goods inventory occurs in this process. Occasionally, however, such unsold finished items (called “orphans” here) are generated. Since their holding cost is substantial, especially if they are physically large and hard to store, the orphans become a serious managerial problem. The dilemma management faces with an orphan is: should the orphan be modified (to the specifications of a new order) to dispose of it now, perhaps even at a loss, or should it be held another period (thereby incurring the substantial holding cost) for a possibly better matching order with a more tolerable modification cost?To meet this management challenge we formulate the dilemma as a stochastic dynamic programming problem, similar to the well-known optimal stopping problem. We obtain optimal policies and analyze their properties for the typical case where there is only one orphan. Last, we extend the approach to the case of multiple orphans for those rare instances when there may be more than one orphan.