TY - GEN

T1 - A customized branch and bound algorithm to solve the resource-sharing and scheduling problem (RSSP)

AU - Ainbinder, Inessa

AU - Pinto, Gaby

AU - Rabinowitz, Gad

AU - Ben-Dov, Yariv T.

PY - 2006/12/1

Y1 - 2006/12/1

N2 - We propose a customized branch and bound (B&B) algorithm (which we refer to as B&B#2) to solve the resource-sharing and scheduling problem (RSSP). The RSSP has previously been formulated as a continuous-time mixed-integer linear programming model and was optimally solved using a branch-and-bound (B&B) algorithm (which we refer to as B&B#1). The RSSP considers the use of a set of resources for the production of several products. Producing each product requires a set of operations with precedence relationships among them. Each operation can be performed using alternative modes which define the subset of resources needed. An operation may share different resources simultaneously. The problem is to select a single mode for each operation (i.e., the allocation decision) and accordingly to schedule the resources (i.e., the sequencing decision) while minimizing the makespan time. The B&B algorithm we propose is based on a minimal branching process at the allocation decision level. We compare the runtime of B&B#2 algorithm versus B&B#1 algorithm on a set of problem instances. The results showed that the average runtime of the B&B#2 algorithm was the smallest.

AB - We propose a customized branch and bound (B&B) algorithm (which we refer to as B&B#2) to solve the resource-sharing and scheduling problem (RSSP). The RSSP has previously been formulated as a continuous-time mixed-integer linear programming model and was optimally solved using a branch-and-bound (B&B) algorithm (which we refer to as B&B#1). The RSSP considers the use of a set of resources for the production of several products. Producing each product requires a set of operations with precedence relationships among them. Each operation can be performed using alternative modes which define the subset of resources needed. An operation may share different resources simultaneously. The problem is to select a single mode for each operation (i.e., the allocation decision) and accordingly to schedule the resources (i.e., the sequencing decision) while minimizing the makespan time. The B&B algorithm we propose is based on a minimal branching process at the allocation decision level. We compare the runtime of B&B#2 algorithm versus B&B#1 algorithm on a set of problem instances. The results showed that the average runtime of the B&B#2 algorithm was the smallest.

UR - http://www.scopus.com/inward/record.url?scp=50249086944&partnerID=8YFLogxK

U2 - 10.1109/ICCCYB.2006.305719

DO - 10.1109/ICCCYB.2006.305719

M3 - Conference contribution

AN - SCOPUS:50249086944

SN - 1424400716

SN - 9781424400713

T3 - 2006 IEEE International Conference on Computational Cybernetics, ICCC

BT - 2006 IEEE International Conference on Computational Cybernetics, ICCC

T2 - 2006 IEEE International Conference on Computational Cybernetics, ICCC

Y2 - 20 August 2006 through 22 August 2006

ER -