GAMS [ Home | Support | Sales | Solvers | Documentation | Model Libraries | Search | Contact Us ]

logmip4.gms : LogMIP User's Manual Example 4 - Job Shop Scheduling

This model solves a jobshop scheduling, which has a set of jobs (5)
which must be processed in sequence of stages (5) but not all jobs
require all stages. A zero wait transfer policy is assumed between
stages. To obtain a feasible solution it is necessary to eliminate
all clashes between jobs. It requires that no two jobs be performed
at any stage at any time. The objective is to minimize the makespan,
the time to complete all jobs.

References:

Raman & Grossmann, Computers and Chemical Engineering 18, 7, p.563-578, 1994.

Aldo Vecchietti, LogMIP User's Manual, http://www.logmip.ceride.gov.ar/, 2007
References:
Large Model of Types: LOGMIP mip
$title LogMIP User's Manual Example 4 - Job Shop Scheduling (LOGMIP4,SEQ=337) $ontext This model solves a jobshop scheduling, which has a set of jobs (5) which must be processed in sequence of stages (5) but not all jobs require all stages. A zero wait transfer policy is assumed between stages. To obtain a feasible solution it is necessary to eliminate all clashes between jobs. It requires that no two jobs be performed at any stage at any time. The objective is to minimize the makespan, the time to complete all jobs. References: Raman & Grossmann, Computers and Chemical Engineering 18, 7, p.563-578, 1994. Aldo Vecchietti, LogMIP User's Manual, http://www.logmip.ceride.gov.ar/, 2007 $offtext SETS I jobs / A, B, C, D, E, F, G / J stages / 1*5 /; ALIAS (I,K),(J,M); SET L(I,K,J) Subset to prevent clasges at stage j between stage j and k /A.B.3, A.B.5, A.C.1, A.D.3, A.E.3, A.E.5, A.F.1, A.F.3, A.G.5, B.C.2, B.D.2, B.D.3, B.E.2, B.E.3, B.E.5, B.F.3, B.G.2, B.G.5, C.D.2, C.D.4, C.E.2, C.F.1, C.F.4, C.G.2, C.G.4, D.E.2, D.E.3, D.F.3, D.F.4, D.G.2, D.G.4, E.F.3, E.G.2, E.G.5, F.G.4 / ; TABLE TAU(I,J) processing time of job i in stage j 1 2 3 4 5 A 3 5 2 B 3 4 3 C 6 3 6 D 8 5 1 E 4 6 2 F 2 5 7 G 8 5 4 ; VARIABLE MS makespan ; BINARY VARIABLE Y(I,K,J) sequencing variable between jobs i and k ; POSITIVE VARIABLE T(I) ; EQUATIONS FEAS(I) makespan greater than all processing times NOCLASH1(I,K,J) when i precedes k NOCLASH2(I,K,J) when k precedes i DUMMY ; FEAS(I).. MS =G= T(I) + SUM(M, TAU(I,M)) ; NOCLASH1(I,K,J)$((ORD(I) LT ORD(K)) AND L(I,K,J)) .. T(I) + SUM(M$(ORD(M) LE ORD(J)), TAU(I,M)) =L= T(K) + SUM(M$(ORD(M) LT ORD(J)), TAU(K,M)); NOCLASH2(I,K,J)$((ORD(I) LT ORD(K)) AND L(I,K,J)) .. T(K) + SUM(M$(ORD(M) LE ORD(J)), TAU(K,M)) =L= T(I) + SUM(M$(ORD(M) LT ORD(J)), TAU(I,M)); DUMMY.. SUM((I,K,J), Y(I,K,J)) =G= 0; MODEL JOBSHOP / ALL / ; $onecho > "%lm.info%" DISJUNCTION D1(I,K,J); D1(I,K,J) with ((ord(I) lt ord(K)) and L(I,K,J)) IS IF Y(I,K,J) THEN NOCLASH1(I,K,J); ELSE NOCLASH2(I,K,J); ENDIF; $OFFECHO T.up(I)=100.; OPTION MIP = LMBIGM, OPTCR = 0.0, OPTCA = 0.0; SOLVE JOBSHOP MINIMIZING MS USING MIP ; DISPLAY Y.L, T.L ;