AN OPTIMAL SOLUTION ALGORITHM FOR THE CONSTANT LOT-SIZE MODEL WITH EQUAL AND UNEQUAL SIZED BATCH SHIPMENTS FOR THE SINGLE-PRODUCT MULTISTAGE PRODUCTION SYSTEM
Ma. Hoque et Bg. Kingsman, AN OPTIMAL SOLUTION ALGORITHM FOR THE CONSTANT LOT-SIZE MODEL WITH EQUAL AND UNEQUAL SIZED BATCH SHIPMENTS FOR THE SINGLE-PRODUCT MULTISTAGE PRODUCTION SYSTEM, International journal of production economics, 42(2), 1995, pp. 161-174
This paper presents a new heuristic solution procedure for the constan
t lot-size model for the production of a single product requiring proc
essing through a fixed sequence of manufacturing stages. There is a si
ngle set-up at each production stage followed by continuous production
of the whole lot. However, the lot may be transferred to subsequent s
tages in partial lots, a set of possibly unequal batches, which may va
ry in size between production stages. Previous models have used a heur
istic solution procedure based on the concept of differentiation of th
e cost function, the sum of the costs of set-up, transportation and in
ventory. This approach has drawbacks when many of the parameters have
to be integer. It also implicitly assumes the cost is a convex functio
n of the lot size. In this situation it can be shown that the function
may often be non-convex. Furthermore, the heuristic does not provide
a solution directly when the production rates of machines in adjacent
stages are equal, and is also unable to consider zero transportation c
ost. By formulating the constraint that the largest batch size at any
stage does not exceed the transport equipment capacity in a different
way, a number of properties that the optimal solution should satisfy a
re developed. An algorithm giving the optimal solution is then derived
based on these properties. This is illustrated by numerical examples,
which indicate further cost reductions on the most recent models prop
osed are possible. This modified model and solution enables the sensit
ivity of the total cost to variations in lot size around the optimal v
alue to be investigated.