ดาวน์โหลด All Proceeding - AS Nida

Table 2. Brief summary on the recent JSSP articles classifying into four categories.
Category Approaches Authors How Results
Heuristic rules
Mathematical
programming
Neighbourhood
search methods
Artificial
intelligence
Dispatching
rules
Branch and
Bound method
Lagrangian
relaxation
Tabu Search
Simulated
Annealing (SA)
Artificial Neural
Network
Holthaus and
Rajendran [17]
Dabbas et al. [18]
Artigues and
Feillet [3]
Artigues et al. [4]
Baptiste et al. [5]
Chen and Luh [6]
Gröflin and
Klinkert [7]
Zhang and Wu [8]
Yang et al. [19]
Yang and Wang
[20]
Fuzzy logic Bilkay et al. [21]
Petri net
Nakamura et al.
[22]
Presented five new dispatching rules for
scheduling in a job shop
Proposed a modified dispatching rule that
combines multiple dispatching criteria into
a single rule
Proposed a new method based on iterative
solving via branch and bound decisional
versions
Proposed an insertion heuristic and
generalized resource constraint
propagation mechanism.
Compared two Lagrangian relaxations for
the job shop
Developed a new Lagrangian relaxation
approach for JSSP
Integrated the neighbourhood in TS
method and reported quite favourably with
benchmark results
Designed a neighbourhood structure based
on blocks for solving JSSP
Presented an improved constraint
satisfaction adaptive neural network (NN)
for JSSP
Proposed a new hybrid approach,
combining CSANN and two heuristics, for
JSSP
Proposed a fuzzy logic-based algorithm for
assigning priorities to part types that are to
be machined
Proposed an evolutionary method to solve
the problem approximated by generating
the Petri net structure
92
These rules are found to be quite
good in minimizing the mean flow
time
Reduced cycle times and lateness
This method allows to close
previously unsolved benchmark
Results prove the constraint
propagation generalisation when
time lags are considered
These results show that these
problems are greatly intractable
New approach is efficient for large
problems with long time horizons
Solutions improve most of
benchmark result found in this paper
New neighbourhood promotes the
searching capability of SA and helps
it convergence
Outperform the original adaptive NN
in term of computational time and
the quality of schedules
Excellent performance respects to
the quality of solutions and the speed
of calculation.
Proposed algorithm improves the
system efficiency
Experimental evaluation show the
effectiveness of approach