A DECOMPOSITION-BASED HEURISTIC ALGORITHM FOR PARALLEL BATCH PROCESSING PROBLEM WITH TIME WINDOW CONSTRAINT

This study considers a parallel batch processing problem to minimize the makespan under constraints of arbitrary lot sizes, start time window and incompatible families. We first formulate the problem with a mixed-integer programming model. Due to the NP-hardness of the problem, we develop a decomposition-based heuristic to obtain a near-optimal solution for large-scale problems when computational time is a concern. A two-dimensional saving function is introduced to quantify the value of time and capacity space wasted. Computational experiments show that the proposed heuristic performs well and can deal with large-scale problems efficiently within a reasonable computational time. For the small-size problems, the percentage of achieving optimal solutions by the DH is 94.17%, which indicates that the proposed heuristic is very good in solving small-size problems. For large-scale problems, our proposed heuristic outperforms an existing heuristic from the literature in terms of solution quality

Channel coordination, trade credit and quantity discounts for freight cost

In this paper we consider vendor-buyer channels subject to trade credit and quantity discounts for freight cost. We deal with the problems of determining the vendor's credit period, the buyer's retail price and order quantity while still maximizing profits. We focus on how channel coordination can be achieved using trade credit and how trade credit can be affected by quantity discounts for freight cost. We show that profits for both parties increase under channel coordination when the credit period is kept within an appropriate range. This range becomes wider as the discount for freight rates increases.Channel coordination Quantity discounts Freight cost Trade credit