prodschx.gms : Production Scheduling Model using SOS1 and SOS2

Description

A company specializing in the manufacture of outboard motors faces
highly seasonal demands and wants to minimize production cost. The
three main cost categories are:
  1. direct production cost (nonlinear production relations and shift
     operations are possible)
  2. inventory cost (rent or lease option)
  3. workforce fluctuation cost.


Reference

  • CDC, APEX-III Reference Manual Version 1.2, Control Data Corporation, Minneapolis, 1980. MIP Sample Problem

Small Model of Type : MIP


Category : GAMS Model library


Main file : prodschx.gms

$title Production Scheduling Model using SOS1 and SOS2 (PRODSCHX,SEQ=109)

$onText
A company specializing in the manufacture of outboard motors faces
highly seasonal demands and wants to minimize production cost. The
three main cost categories are:
  1. direct production cost (nonlinear production relations and shift
     operations are possible)
  2. inventory cost (rent or lease option)
  3. workforce fluctuation cost.


CDC, APEX-III Reference Manual Version 1.2, Control Data Corporation,
Minneapolis, 1980. MIP Sample Problem

This is a revised version of the model PRODSCH (SEQ=9). The GAMS
SOS definition required to change the index positions of the
variables ss and SSB. There are three possible ways to use a MIP.

Keywords: mixed integer linear programming, special ordered sets, production
          problem, scheduling
$offText

* Binary variables
* SOS1 sets
* SOS2 sets
* Some equations are entered twice with a different name to comply
* with the strict typing of variables in GAMS.

Set
   q       'quarters'                           / summer, fall, winter, spring /
   s       'shifts'                             / first, second /
   l       'production levels'                  / 1*4 /
   i(l)    'production level intervals'         / 1*3 /;

Parameter
   d(q)    'demand         (motors per season)' / spring 24000 /
   delt(q) 'discount factor'
   lc(q)   'leasing cost  (dollars per season)' / summer 15000 /
   ei(q)   'initial employment'                 / summer    84 /;

Scalar
   mc      'material cost  (dollars per motor)' / 100 /
   sr      'space rental   (dollars per motor)' /   2 /
   invmax  'upper bound on inventory  (motors)'
   hc      'hiring cost (dollars per employee)' / 900 /
   fc      'firing cost (dollars per employee)' / 150 /;

delt(q) = 1/1.03**(ord(q)-1);
invmax  = sum(q, d(q));

Table pr(*,l) 'production relationship'
                  1      2      3      4
   labor         20     40     50     60
   motor       1000   3000   4500   5800;

Table sc(*,s) 'shift cost (dollars per shift)'
               first    second
   fixed       10000     16000
   labor        3500      4100;

Variable
   cost       'total discounted cost per year         (1000 $)'
   dpc(q)     'direct production cost      (1000 $ per season)'
   isc(q)     'inventory storage cost      (1000 $ per season)'
   wfc(q)     'workforce fluctuation cost  (1000 $ per season)'
   src(q)     'space rental cost           (1000 $ per season)'
   p(q)       'production                  (motors per season)'
   ss(q,s,l)  'production segments                 (sos2 type)'
   ssb(q,s,l) '0-1 needed for ss sos2 formulation'
   ss1(q,s,l) 'SOS1 needed for ss sos2'
   ss2(q,s,l) 'SOS2 formulation'
   inv(q)     'inventory                   (motors per season)'
   lease      'lease-rent option'
   e(q)       'total employment                    (employees)'
   se(q,s)    'shift employment          (employees per shift)'
   shift(q,s) 'shift use indicator                    (binary)'
   h(q)       'hirings per quarter                 (employees)'
   f(q)       'firings per quarter                 (employees)';

Positive Variable p, ss, inv, src, h, f;

Binary   Variable lease, shift, ssb;

SOS1 Variable ss1;
SOS2 Variable ss2;

Equation
   acost       'total cost definition                 (1000 $)'
   ddpc(q)     'direct production cost definition     (1000 $)'
   disc(q)     'inventory storage cost definition     (1000 $)'
   dwfc(q)     'workforce fluctuation cost definition (1000 $)'
   sbp(q)      'sos product balance                   (motors)'
   sbps2(q)    'SOS2 product balance                   motors)'
   sbse(q,s)   'sos shift employment balance       (employees)'
   sbses2(q,s) 'SOS2 shift employment balance      (employees)'
   scc(q,s)    'sos shift link'
   sccs2(q,s)  'SOS2 shift link'
   invb(q)     'inventory balance                     (motors)'
   dsrc(q)     'definition: space rental'
   ed(q)       'total employment definition        (employees)'
   eb1(q)      'employment balance type 1          (employees)'
   eb2(q)      'employment balance type 2          (employees)'
   messb(q,s)  'mutual exclusivity for ssb'
   mess1(q,s)  'mutual exclusivity for ss1'
   lssb(q,s,l) 'ss - ssb linkage'
   lss1(q,s,l) 'ss - ss1 linkage';

acost..       cost    =e= sum(q, delt(q)*( dpc(q) + isc(q) + wfc(q) ));

ddpc(q)..     dpc(q)  =e= (mc*p(q) + sum(s, sc("fixed",s)*shift(q,s) + sc("labor",s)*se(q,s)))/1000;

sbp(q)..      p(q)    =e= sum((s,l), pr("motor",l)*ss (q,s,l));
sbps2(q)..    p(q)    =e= sum((s,l), pr("motor",l)*ss2(q,s,l));

sbse(q,s)..   se(q,s) =e= sum(l, pr("labor",l)*ss (q,s,l));
sbses2(q,s).. se(q,s) =e= sum(l, pr("labor",l)*ss2(q,s,l));

scc(q,s)..    sum(l, ss (q,s,l)) =e= shift(q,s);
sccs2(q,s)..  sum(l, ss2(q,s,l)) =e= shift(q,s);

invb(q)..     inv(q) =e= inv(q-1) + p(q) - d(q);

disc(q)..     isc(q) =e= (lc(q)*lease + src(q))/1000;

dsrc(q)..     src(q) =g= sr*( inv(q) - invmax*lease );

dwfc(q)..     wfc(q) =e= (hc*h(q) + fc*f(q))/1000;

ed(q)..       e(q)   =e= sum(s, se(q,s));

eb1(q)..      e(q)   =e= e(q-1) + h(q) - f(q) + ei(q);
eb2(q)..      e(q)   =e= e(q--1) + h(q) - f(q);

messb(q,s)..  sum(l, ssb(q,s,l)) =e= 1;
mess1(q,s)..  sum(l, ss1(q,s,l)) =e= 1;

lssb(q,s,l).. ss(q,s,l-1) + ss(q,s,l) =l= ssb(q,s,l-2) + ssb(q,s,l-1) + ssb(q,s,l);
lss1(q,s,l).. ss(q,s,l-1) + ss(q,s,l) =l= ss1(q,s,l-2) + ss1(q,s,l-1) + ss1(q,s,l);

p.up("spring") = .8*card(s)*smax(l, pr("motor",l));

Model
   prod1B  'initial employment' / acost, ddpc, sbp, sbse, scc, disc, invb, dsrc, dwfc, ed, eb1, messb, lssb /
   prod2B  'steady state'       / acost, ddpc, sbp, sbse, scc, disc, invb, dsrc, dwfc, ed, eb2, messb, lssb /
   prod1S1 'initial employment' / acost, ddpc, sbp, sbse, scc, disc, invb, dsrc, dwfc, ed, eb1, mess1, lss1 /
   prod2S1 'steady state'       / acost, ddpc, sbp, sbse, scc, disc, invb, dsrc, dwfc, ed, eb2, mess1, lss1 /
   prod1S2 'initial employment' / acost, ddpc, sbps2, sbses2, sccs2, disc, invb, dsrc, dwfc, ed, eb1 /
   prod2S2 'steady state'       / acost, ddpc, sbps2, sbses2, sccs2, disc, invb, dsrc, dwfc, ed, eb2 /;

* get global optimum (OPTCR) and force each solve to start from scratch (BRATIO)
option optCr = 0, limCol = 0, limRow = 0, bRatio = 1;

Parameter report 'summary performance report';

solve prod1b minimizing cost using mip;
report('prod1b','objval')   = prod1b.objval;
report('prod1b','iterusd')  = prod1b.iterusd;
report('prod1b','nodusd')   = prod1b.nodusd;

solve prod1s1 minimizing cost using mip;
report('prod1s1','objval')  = prod1s1.objval;
report('prod1s1','iterusd') = prod1s1.iterusd;
report('prod1s1','nodusd')  = prod1s1.nodusd;

solve prod1s2 minimizing cost using mip;
report('prod1s2','objval')  = prod1s2.objval;
report('prod1s2','iterusd') = prod1s2.iterusd;
report('prod1s2','nodusd')  = prod1s2.nodusd;

solve prod2b  minimizing cost using mip;
report('prod2b','objval')   = prod2b.objval;
report('prod2b','iterusd')  = prod2b.iterusd;
report('prod2b','nodusd')   = prod2b.nodusd;

solve prod2s1 minimizing cost using mip;
report('prod2s1','objval')  = prod2s1.objval;
report('prod2s1','iterusd') = prod2s1.iterusd;
report('prod2s1','nodusd')  = prod2s1.nodusd;

solve prod2s2 minimizing cost using mip;
report('prod2s2','objval')  = prod2s2.objval;
report('prod2s2','iterusd') = prod2s2.iterusd;
report('prod2s2','nodusd')  = prod2s2.nodusd;

display report;