For Forging Furnace Installed Energy Portfolio Optimization Problems

The global energy supply is increasingly intensive, thus energy saving has become a heated topic for research. As a major energy consumer, the manufacturing industry would have more responsibility in energy saving. In this case, this article conducts energy saving studies over forge industry via scheduling. It selects heating batch as the study objective, points out time range/temperature range and furthermore discusses batching method respectively.1. The energy saving study of forge batch sequence based on weight-matching rules. The study establishes mathematical models according to detailed problem descriptions, and focuses on workpiece sets with similar holding temperatures and time but different unit weights. It furthermore develops a genetic algorithm based on batch weight-matching rules. Finally with the comparison of practical statistics from the method above and traditional manual method, the study verifies the effectiveness and advantage of the batching method above.2. The energy saving study of forge batch sequence considering temperature range. The study focuses on workpiece sets with similar holding time but different temperatures and unit weights. The study firstly states that holding temperature in practical production has a moving range. Secondly, it introduces temperature compatibility in problem description and establishes mathematical models accordingly. Thirdly, the study develops a genetic algorithm based on temperature compatibility. Last, it verifies the effectiveness of above method by applying practical statistics and proves its advantage over traditional manual methods.3. The energy saving study of forge batch sequence considering time and temperature ranges. The study focuses on workpiece sets with different holding time, temperatures and unit weights. The study firstly states that holding time has a moving range as well as temperature. Secondly, it introduces time compatibility and same-batch-heating rules in problem description and establishes mathematical models accordingly. Thirdly, the study develops a discrete shuffled frog leaping algorithm based on same-batch-heating rules. Last, it verifies the effectiveness of above method by applying practical statistics and proves its advantage over traditional manual methods.