Modelling Process and Supply Chain Scheduling Using Hybrid Meta-heuristics

This chapter proposes a natural stigmergic computational technique Bee Colony for process scheduling and optimization problems developed by mimicking social insects’ behavior. The case study considered in the chapter is a milk production center, where process scheduling, supply chain network etc. are crucial, as slight deviation in scheduling may lead to perish out the item causing financial loss of the plant. The process scheduling of such plants extensively deals with multi-objective conflicting criteria, hence the concept of Pareto Dominance has been introduced in the form of Pareto Bee Colony Optimization. Some facts about social insects namely bees are presented with an emphasis on how they could interact and self organized for solving real world problems. Finally, a performance simulation and comparison has been accomplished envisaging other similar bio-inspired algorithms.

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