Informatica

We study an inventory control problem of a perishable product with a fixed short shelf life in Dutch retail practice. The demand is non-stationary during the week but stationary over the weeks, with mixed LIFO and FIFO withdrawal. The supermarket uses a service level requirement. A difficulty is that the age-distribution of products in stock is not always known. Hence, the challenge is to derive practical and efficient order policies that deal with situations where this information is either available or lacking. We present the optimal policy in case the age distribution is known, and compare it with benchmarks from literature. Three heuristics have been developed that do not require product age information, to align with the situation in practice. Subsequently, the performance of the heuristics is evaluated using demand patterns from practice. It appears that the so-called STIP heuristic (S for Total estimated Inventory of Perishables) provides the lowest cost and waste levels.

This paper investigates the problem of partitioning a complete weighted graph into complete subgraphs, each having the same number of vertices, with the objective of minimizing the sum of edge weights of the resulting subgraphs. This NP-complete problem arises in many applications such as assignment and scheduling-related group partitioning problems and micro-aggregation techniques. In this paper, we present a mathematical programming model and propose a complementary column generation approach to solve the resulting model. A dual based lower bounding feature is also introduced to curtail the notorious tailing-off effects often induced when using column generation methods. Computational results are presented for a wide range of test problems.

This paper is concerned with an employee scheduling problem involving multiple shifts and work centers, where employees belong to a hierarchy of categories having downward substitutability. An employee at a higher category may perform the duties of an employee at a lower category, but not vice versa. However, a higher category employee receives a higher compensation than a lower category employee. For a given work center, the demand for each category during a given shift is fixed for the weekdays, and may differ from that on weekends. Two objectives need to be achieved: The first is to find a minimum-cost workforce mix of categories of employees that is needed to satisfy specified demand requirements, and the second is to assign the selected employees to shifts and work centers taking into consideration their preferences for shifts, work centers, and off-days. A mixed-integer programming model is initially developed for the problem, based on which a specialized scheduling heuristic is subsequently developed for the problem. Computational results reported reveal that the proposed heuristic determines solutions proven to lie within 92–99% of optimality for a number of realistic test problems.