S. Breitinger and H.C.R. Lock. Using Constraint Logic Programming for Industrial Scheduling Problem, chapter 9. Elsevier Science B.V, 1995.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....We can deduce that this constraint is very tight. On the other hand, suppose we have one more long duty to be assigned. Then the constraint on long duties is very loose. In this way, we can exploit a heuristic which is similar to the one used for the bottleneck analysis in scheduling problems [1]. We select first those duties which play the most important part in the tightest constraints, those being the bottlenecks of our problem. As concerns the problem symmetries, we can identify two different kinds: symmetries on the overall rostering, due to the fact that the solution (Roster A , ....

S. Breitinger and H.C.R. Lock. Using Constraint Logic Programming for Industrial Scheduling Problem, chapter 9. Elsevier Science B.V, 1995.

....successful practical applications solving difficult and commercially important real world problems. Examples include scheduling for factories and for computer instruction sets; financial applications such as options and portfolio analysis; and modelling water usage, DNA, and electrical circuits [3, 10, 23, 24, 38, 39, 64, 72, 78, 79, 86]. Many problems which previously appeared local to a particular application domain, and which were therefore solved in an ad hoc manner, can now be seen as instances of constraint problems. For example, AI applications as disparate as machine vision and belief revision can now be considered in ....

S. Breitinger and H. C. R. Lock. Using Constraint Logic Programming for Industrial Scheduling Problems. In C. Beierle and L. Plumer, editors, Logic Programming: Formal Methods and Practical Applications, chapter 9, pages 273--299. Elsevier, 1995.

....Difficult combinatorial problems which were previously intractable to logic programs could now be expressed cleanly in CLP and solved with the power of well known constraint techniques. Hence the uses of CLP are varied, and include building VLSI CAD tools [BBM94] industrial scheduling [DSH90, BL95] shift planning [WV93] and satellite altitude determination [Sku94] amongst others. The introduction of constraints into logic programming, however, requires another look at the underlying theory. Recall that PROLOG treats all basic objects as uninterpreted, pure symbols, and that unification is ....

S. Breitinger and H.C.R. Lock. Using constraint logic programming for industrial scheduling problems. In C. Beierle and L. Plumer, editors, Logic Programming: Formal Methods and Practical Applications, chapter 9, pages 273--299. Elsevier Science, 1995.

....which values of each variable are compatible. A solution of a CSP is an assignment of values to all variables, which satisfies all the constraints. The class of CSP involves different application areas such as planning, scheduling, resource allocation, assignment, placement and logistics [2, 6, 7, 19, 14]. They are characterized by common features. For instance, there is no efficient way of solving them as they often belong to the NP complete class of problems. Therefore, different strategies and heuristic rules have been tested. Solutions to these problems based on imperative languages are ....

....is equal to the rate at which the liquid can flow through the narrowest portion of the pipe. In dealing with scheduling problems a very useful strategy is to identify bottlenecks in the flow of material and try to schedule those bottlenecks first, in order to obtain the highest throughput, see [2]. In a CRP, performing a bottleneck analysis means detecting the most difficult constraint that has to be satisfied, and trying to handle first those duties which participate most in that constraint. A simple example is the following: suppose we have a problem P defined by the set of duties D. ....

S. Breitinger and H.C.R. Lock. Using Constraint Logic Programming for Industrial Scheduling Problem, chapter 9. Elsevier Science B.V, 1995.

....heuristic plus the cost of getting to that state (thus we are doing A search) each problem requires 94 seconds to solve. 9 When using IDA (with the same heuristic) they took only 32 seconds each. In the job shop domain we experimented with a hard 10 Theta 10 benchmark problem (given in [BL94] ) Heuristic Breadthfirst and IDA search are ineffective as the problem is too hard for the simple heuristic outlined in Section 5. However, the job shop domain has the property that every path in the search tree terminates with a feasible schedule. Thus we can employ depth first branch and ....

....search on the optimal heuristic bound. Such a strategy can also be implemented with a formula, and it finds a schedule of length 1178 (in 968.9 sec. The times and schedules we obtained are competitive with the application of constraint logic programming to solve this problem as reported in [BL94] . 7 Conclusions We have described a search system that is based on the idea of evaluating first order formulas over finite models. We have applied the system to a range of search problems, of which we have only mentioned two prototypical problems. Putting a formula evaluator at the core of the ....

Silvia Breitinger and Hendirck C. R. Lock. Using constraint logic programming for industrial scheduling problems. In C. Beierle and L. Plumer, editors, Logic Programming: Formal Methods and Practical Applications. Elsevier, 1994.

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