[Python] Why the result is infeasible?

I have spent much time trying to solve the problem below, and I think the solution is very obvious. Suppose I have a set of jobs, each needing one mold; changing from mold A to mold B has a cost. I want to search for the job sequence that minimizes the mold change cost.

job mold



Mold shift cost



My code is as follows:

%pip install -q amplpy

SOLVER = "highs"

from amplpy import AMPL, ampl_notebook

ampl = ampl_notebook(
modules=["highs"], # modules to install
license_uuid="default", # license to use
) # instantiate AMPL object and register magics


import pandas as pd

jobmold = pd.DataFrame(
{
"Job1": {"mold": 1},
"Job2": {"mold": 2},
"Job3": {"mold": 1},
"Job4": {"mold": 3},
"Job5": {"mold": 2},
"Job6": {"mold": 3},
"Job7": {"mold": 2},
}
).T

moldshiftcost = pd.DataFrame(
{
"mold1": {"mold1": 0, "mold2": 2, "mold3": 4},
"mold2": {"mold1": 2, "mold2": 0, "mold3": 4},
"mold3": {"mold1": 7, "mold2": 1, "mold3": 0}
}
).T

display(jobmold)
display(moldshiftcost)


%%writefile LPanelProduction.mod
set JOBS;
set MOLDS;
set jobpairs within {JOBS,JOBS};
set moldpairs within {MOLDS,MOLDS};
set SHIFTJOBS;

param jobshiftcost{jobpairs};
param moldshiftcost{moldpairs};
param jn;
param mn;
param shiftnum;

var sequence{JOBS} integer >=0,<jn

minimize obj:sum{k in SHIFTJOBS, i in JOBS, j in JOBS}(if sequence[k]==i and sequence[k+1]==j then 1 else 0)*jobshiftcost[i,j];

subj to no_overlap{i in JOBS, j in JOBS}sequence> sequence[j] or sequence<sequence[j]);


def Lpanelproduction(jobmold, moldshiftcost):
model = AMPL()
model.read("LPanelProduction.mod")

jn = len(jobmold)
JOBS = range(jn)
SHIFTJOBS = range(jn - 1)
shiftnum = len(SHIFTJOBS)
jobpairs = {(i, j) for i in JOBS for j in JOBS}

model.param["jn"] = jn
model.set["JOBS"] = JOBS
model.set["SHIFTJOBS"] = SHIFTJOBS
model.set["jobpairs"] = jobpairs
model.param["shiftnum"] = shiftnum

mn = len(moldshiftcost)
MOLDS = range(mn)
moldpairs = {(i, j) for i in MOLDS for j in MOLDS}

model.param["mn"] = mn
model.set["MOLDS"] = MOLDS
model.set["moldpairs"] = moldpairs

moldshiftcost = moldshiftcost.values
model.param["moldshiftcost"] = moldshiftcost

jobmold = jobmold.values

jobshiftcost = {(i, j): moldshiftcost[(k, l)].tolist() for (i, j) in jobpairs for (k, l) in moldpairs if
(jobmold - 1) == k and (jobmold[j] - 1) == l}
model.param["jobshiftcost"] = jobshiftcost

return model


y = Lpanelproduction(jobmold, moldshiftcost)
y.solve(solver=SOLVER)
assert y.solve_result == "solved", y.solve_result

y.display("sequence")


I have spent a lot of time but I cannot find out what is wrong with my code. Why can't I obtain a feasible solution? I am very puzzled. Hope anyone can help me out. Thank you.

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