CHANCE CONSTRAINED PROGRAMMING MODELS FOR RISK-BASED ECONOMIC AND POLICY ANALYSIS OF SOIL CONSERVATION

The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models can provide information on the trade-offs among pre-determined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.Risk and Uncertainty,

A heuristic to minimize total flow time in permutation flow shop

In this paper, we address an n-job, m-machine permutation flow shop scheduling problem for the objective of minimizing the total flow time. We propose a modification of the best-known method of Framinan and Leisten [An efficient constructive heuristic for flowtime minimization in permutation flow shops. Omega 2003;31:311-7] for this problem. We show, through computational experimentation, that this modification significantly improves its performance while not affecting its time-complexity.Flow shop scheduling Total flow time Heuristic procedure

Evaluation of the potential benefits of lot streaming in flow-shop systems

Lot streaming is the process of splitting a production lot into sublots, and then scheduling the sublots in overlapping fashion on the machines, in order to improve the overall performance of the production system. Simulation-based and industry-based reports have confirmed that substantial benefits are possible via lot streaming. In this paper, we present, for the first time, analytical results pertaining to the potential benefits of lot streaming in flow-shop systems. The results are developed using three common performance measures. These measures are (a) makespan (i.e., the total completion time of all the lots), (b) mean flow time, and (c) average WIP level. For each, an expression of the ratio of the measure under lot streaming to the measure without lot streaming is developed. These expressions can be used to evaluate the benefits of lot streaming under certain operating conditions. It is further shown that, in special extreme cases, these expressions purely depend upon the problem parameters (i.e., the number of machines, the number of lots, the lot-sizes, etc.

A near-optimal heuristic for the sequencing problem in multiple-batch flow-shops with small equal sublots

In this paper, we consider the lot-streaming problem of sequencing a set of batches, to be processed in equal sublots, in a flow-shop, so as to minimize makespan. A new heuristic procedure, called the bottleneck minimal idleness heuristic, is developed. Results of an experimental study are presented. It is shown that the proposed procedure generates solutions that are very close to the optimal solutions, and that the solutions generated are better than those obtained by using the fast insertion heuristic, considered to be a good heuristic for solving the flow-shop scheduling problem, when applied to the problem on hand.

A method for reducing inter-departure time variability in serial production lines

The inter-departure time variability is an important measure in production lines. Higher variability means added work-in-process and less predictability in output. It can be a primary obstacle towards achieving on-time delivery. The effects of line parameters (e.g., line length or buffer capacity) on inter-departure time variability have been studied in recent years but no method has been proposed for its reduction. In this paper, such a strategy is proposed and studied via simulation. Results indicate that significant reductions (of more than 20%) in inter-departure time variability can be achieved for as little as 0.5% increase in the mean inter-departure time or without any increase at all, for a majority of the line parameter values experimented. This was found to be the case for symmetrical (uniform) processing time distributions as well as for asymmetrical skewed (exponential) distributions. Similar results have also been obtained in the application of the proposed strategy for the case when one station has a higher variance than the others. Therefore, in situations where output predictability is more of a problem than capacity, this strategy constitutes an effective alternative.Serial production line Buffers Work-in-progress Inter-departure time Simulation