(400b) Integrated Operational Planning and Medium-Term Scheduling for Large-Scale Industrial Semicontinuous/Continuous Processes

The operational
planning and the medium-term scheduling of industrial semicontinuous/continuous
multiproduct processes are closely linked to each other, since both operational
planning and scheduling involve the allocation of plant resources. The operational
planning problem typically determines production targets for the plant to meet product
demands over a long time horizon from one to three months. The medium-term
scheduling problem is defined over a shorter time horizon of between two to
four weeks and involves detailed decisions such as the sequence of processing
units, and detailed timings in which various products should be processed in
each unit to meet the production targets supplied by the operational planning
problem [1-2]. The lack of integration of planning and scheduling often make
the planning model to provide unrealistic production targets causing the
scheduling model to allocate plant resources in a suboptimal manner. The
effective integration of planning and scheduling can increase profits and
reduce committed capital simultaneously [3]. However, because of their
disparate time scales, the effective integration of planning and scheduling is
a critically challenging task. Therefore, it is imperative to propose a novel
framework that can integrate the operational planning and scheduling more
effectively.

A simple
approach for solving the integration of planning and scheduling problems is to
develop a single simultaneous planning and scheduling model over the entire the
planning horizon. However, this approach resulted in large problem size for
typical planning horizons, which is often computationally intractable. Therefore,
the integration problem is often solved using bilevel decomposition approach [4],
and rolling horizon algorithm [5]. Shah [6], Kallrath [7], Maravelias and Sung
[8], and Verderame et al. [9] presented excellent reviews on the integration of
planning and scheduling. However, most of the work related to integration of
planning and scheduling has focused on batch processes. Moreover, most of the proposed
operational planning models provide the aggregate production targets, not the daily
production profile required by the scheduling model.

Recently, Verderame
and Floudas [10-15] developed novel discrete-time mixed-integer linear
programming (MILP) operational planning with production disaggregation models (PPDM)
for a large-scale multipurpose and multiproduct batch plant with/without
uncertainty. In their model, they disaggregated the production totals into a
feasible distribution of daily production requirements and hence provided the
daily production profile. They also allowed any unutilized reactor time to
carry over from one day to the next and hence captured the continuous time
nature of the plant. To integrate the operational planning and medium-term scheduling
model developed by Janak et al. [16-17] effectively, they proposed a novel
forward rolling horizon framework that allowed the feedback of scheduling
production leading to additional operational planning model constraints. The computational
results showed that the proposed framework yields greater aggregate production
totals and a higher degree of daily demand satisfaction, compared to the
approach of isolated planning and scheduling, which did not allow the two-way
interaction between planning and scheduling. However, all of their work is also
limited to batch processes.

In this
presentation, we first introduce a novel mixed-integer linear programming
(MILP) operational planning model based on discrete-time representation for large-scale
industrial semicontinuous/continuous multiproduct processes. In the model, we allow
unused processing time to carry over from one day to the next and capture the
continuous time nature of the plant. The production totals are disaggregated
into a feasible distribution of daily production requirements and hence daily
production profiles are provided to meet the requirements of medium-term
scheduling model developed by Shaik and Floudas [18]. The forward rolling
horizon framework proposed by Verderame and Floudas [10-15] is utilized to effectively
address the integration of operational planning and medium-term scheduling
model. The forward rolling horizon framework is applied to an industrial case
study of a large-scale continuous multiproduct plant over a three-month time
horizon. The computational results show that the framework can lead to the
operational planning model providing a tighter upper bound on the production
capacity and a higher degree of daily demand satisfaction compared to the
approach of isolated planning and scheduling.

References

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