New Mixed Integer Linear Programming Model for Solving Scheduling Problems with Special Characteristics

Abstract

A new mixed integer linear programming (MILP) model suitable for optimizing scheduling problems typical in chemical and related industries is developed. These problems have characteristics like storage time constraints, operational connectivity restrictions, and continuous tasks with special precedence constraints. Therefore, a new MILP model is developed for handling these special scheduling problems. The numerical capability of the model is demonstrated using test problems of different complexity levels.

Rolling Operation Algorithm for Solving Complex Scheduling Problems

“…As is shown by Czuczai et al, the model summarized in section works fine for small-scale problems. However, the problem may become unsolvable even for medium-scale processes because of the combinatorial difficulties caused by the need of modeling the connections between units.…”

“…The makespan is not considered at all, i.e., the operations can take any time; the only requirement is that the ou th operation has to be finished before the deadline of order ord if the ou th operation produces product for satisfying order ord . The subproblem includes all the constraints detailed in the paper of Czuczai et al, except the two enforcing the satisfaction of the product orders and consumption of raw materials. The relaxation of the latter two constraints is necessary because there are not enough number of available operations for satisfying all the orders and consuming all the raw materials.…”

“…Based on a different concept, Czuczai et al recently developed a new model. It introduces the notion of operations of units.…”

Case-Based Reasoning system for mathematical modelling options and resolution methods for production scheduling problems: Case representation, acquisition and retrieval

“…The case study, first studied by Czuczai, Farkas, Rev, and Lelkes (2009), concerns an industrial process for beer production that is composed of 4 workstations: a draft beer tank, a filter, a bright beer tank, and a workstation with three package lines, Fig. 20.…”

“…The last column of Table 5, i.e. the work of Czuczai et al (2009) gives the description of the modelling option used to solve the case study. For all the solutions d 2 = RTN, which is not surprising at first glance.…”