A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Algorithm 1

Pseudo Code of LGSCPSOA.

Step 1: Initialize parameters; including swarm size PS, end of generation G, and other

   parameters will be used in LGSCPSOA;

Step 2: Segment and scheduling;

 (i)      Generate stochastically initialization population and velocity using Section 3.2.1 coding

      scheme

 (ii)   Evaluate each particle’s fitness

 (iii)Initialize gbest position with the lowest fitness particle in the swarm

 (iv)   Initialize ibest and lbest position with a copy of particle itself

 (v)      𝑘∶=0

 While (the end G of generation is not met)

 {

 (i)     𝑘∶=𝑘+1

 (ii)  Generate next generation particle population by recurrence equations (3.3), (3.4)

     and (3.5)

 (iii)Evaluate swarm

        {(1)Compute each particle’s fitness in the swarm

         (2)Find new 𝑃_𝑔 of the swarm, 𝑃_𝑙 of generation population and 𝑃_𝑖 of each

                 particle by comparison, and update 𝑃_𝑖 and 𝑃_𝑔

          (3)Update 𝑃_𝑙 with (3.5)

             Using the best particle of k generation replace the 𝑘−1 generation u%

             particles which are random selected}

   }

Step 3: Output optimization result 𝑃_𝑔;

End