Taboo search vs genetic algorithms in solving and optimising PCB problems

This is the authors' abstract. We don't add key points for this paper.

Purpose To highlight the differences and common features of taboo search (TS) and genetic algorithms (GA) in solving the problem of board‐type sequencing on the assembly line simultaneously with the combined problem of feeder assignment and component placement sequencing in the printed circuit board (PCB) industry. Design/methodology/approach Two metaheuristics (search techniques) are used to solve three problems associated with the PCB assembly line: TS and GA. The implemented approach is used to solve the three problems on a single pick‐and‐place sequential machine with a stationary board table and stationary feeders, and with the use of the Euclidean metric. Findings The achieved results show a satisfactory reduction in assembly time, when TS and GA are compared with a random solution, with a slight superiority of TS over GA. However, the program running time is longer for TS. Practical implications The hypothetical case study used shows that in real life the savings could reach an average of 6 per cent when TS is used. Slightly lower savings are possible when GA is used. Originality/value This paper provides a clear insight into how some of the problems associated with the production of PCBs can be solved simultaneously using metaheuristics such as TS and GA.