Abstract

The increasing demand of goods, the high competitiveness in the global marketplace as well as the need to minimize the ecological footprint lead multipurpose batch process industries to seek ways to maximize their productivity with a simultaneous reduction of raw materials and utility consumption and efficient use of processing units. Optimal scheduling of their processes can lead facilities towards this direction. Although a great number of mathematical models have been developed for such scheduling, they may still lead to large model sizes and computational time. In this work, we develop two novel mathematical models using the unit-specific event-based modelling approach in which consumption and production tasks related to the same states are allowed to take place at the same event points. The computational results demonstrate that both proposed mathematical models reduce the number of event points required. The proposed unit-specific event-based model is the most efficient since it both requires a smaller number of event points and significantly less computational time in most cases especially for those examples which are computationally expensive from existing models.

Highlights

  • Nowadays, it is more important than ever for multipurpose batch process industry to maximize their productivity by simultaneously minimize their costs, fuel and raw material consumption and ecological footprint to be able to survive in a highly competitive market

  • To avoid an intractable number of time intervals required, continuous-time modelling approaches have been proposed in which the scheduling horizon is divided into ordered slots or event points with non-uniform unknown lengths

  • Shaik and Vooradi [26] proposed a task-specific event-based model for scheduling of multipurpose batch processes, allowing production and consumption tasks related to the same states to take place at the same event points

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Summary

Introduction

It is more important than ever for multipurpose batch process industry to maximize their productivity by simultaneously minimize their costs, fuel and raw material consumption and ecological footprint to be able to survive in a highly competitive market. Shaik and Vooradi [26] proposed a task-specific event-based model for scheduling of multipurpose batch processes, allowing production and consumption tasks related to the same states to take place at the same event points. The model size and computational performance largely depend on the number of event points required This motivates us to develop new mathematical formulations for scheduling of multipurpose batch facilities by allowing consuming and production tasks related to the same states take place at the same event points to reduce the number of event points required. 121 a) SF: the model of Shaik and Floudas [25]; T-S: the revised model of Shaik and Floudas [25] allowing all production and consumption tasks related to the same states take place at the same event points; CPU: Central processing unit; RMILP: relaxed mixed-integer linear program

Model M1
Capacity constraints
Material balance
Processing duration constraints
Sequencing constraints
Objectives
Material balance constraints
Findings
Conclusions
Full Text
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