Pull-tabbing is an evaluation technique for functionallogic programs which computes all non-deterministic results in a single graph structure. Pull-tab steps are local graph transformations to move non-deterministic ...
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the proceedings contain 29 papers. the special focus in this conference is on Integration of constraintprogramming, Artificial Intelligence, and Operations Research. the topics include: the Traveling Social Golfer Pr...
ISBN:
(纸本)9783030782290
the proceedings contain 29 papers. the special focus in this conference is on Integration of constraintprogramming, Artificial Intelligence, and Operations Research. the topics include: the Traveling Social Golfer Problem: the Case of the Volleyball Nations League;Towards a Compact SAT-Based Encoding of Itemset Mining Tasks;a Pipe Routing Hybrid Approach Based on A-Star Search and Linear programming;MDDs Boost Equation Solving on Discrete Dynamical Systems;two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors;Improving the Filtering of Branch-and-Bound MDD Solver;on the Usefulness of Linear Modular Arithmetic in constraintprogramming;injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem;learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems;between Steps: Intermediate Relaxations Between Big-M and Convex Hull Formulations;a Computational Study of constraintprogramming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects;logic-Based Benders Decomposition for an Inter-modal Transportation Problem;checking constraint Satisfaction;finding Subgraphs with Side constraints;Short-Term Scheduling of Production Fleets in Underground Mines Using CP-Based LNS;learning to Reduce State-Expanded Networks for Multi-activity Shift Scheduling;seaPearl: A constraintprogramming Solver Guided by Reinforcement Learning;learning to Sparsify Travelling Salesman Problem Instances;optimized Item Selection to Boost Exploration for Recommender Systems;improving Branch-and-Bound Using Decision Diagrams and Reinforcement Learning;physician Scheduling During a Pandemic;strengthening of Feasibility Cuts in logic-Based Benders Decomposition;learning Variable Activity Initialisation for Lazy Clause Generation Solvers;a * -Based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem;Partitioning Students into Cohorts During
Implementing a complex concept as an executable model in a strongly typed, purely functional language hits a sweet spot between mere simulation and formal specification. For research and education it is often desirabl...
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It is well known in the constraintprogramming community that any non-binary constraint satisfaction problem (with finite domains) can be transformed into an equivalent binary one. One of the most well-known translati...
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the proceedings contain 87 papers. the special focus in this conference is on Declarative programming. the topics include: Concolic testing of functionallogic programs;Declarative XML Schema validation with SWI–Prol...
ISBN:
(纸本)9783030008000
the proceedings contain 87 papers. the special focus in this conference is on Declarative programming. the topics include: Concolic testing of functionallogic programs;Declarative XML Schema validation with SWI–Prolog: System description;plspec – A specification language for prolog data;run-time analysis of temporal constrained objects;implementation of logical retraction in constraint handling rules with justifications;the proportional constraint and its pruning;an operational semantics for constraint-logic imperative programming;hypertree decomposition: the first step towards parallel constraint solving;declarative aspects in explicative data mining for computational sensemaking;an approach for representing answer sets in natural language;Techniques for efficient lazy-grounding ASP solving.
We deal with a challenging scheduling problem on parallel-machines with sequence-dependent setup times and release dates from a real-world application of semiconductor workshop production. there, jobs can only be proc...
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this paper studies a real-life inter-modal freight transportation problem, comprised by three consecutive stages: disposition where orders are picked up by trucks, transferred and unloaded to a set of warehouses in Ce...
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ISBN:
(纸本)9783030782306;9783030782290
this paper studies a real-life inter-modal freight transportation problem, comprised by three consecutive stages: disposition where orders are picked up by trucks, transferred and unloaded to a set of warehouses in Central and Eastern Europe, inter-region transport where the orders are packed into trailers, which are shipped to warehouses in Turkey using different inter-region transport modes, and last-mile delivery where the orders unloaded at the warehouses in Turkey are picked up by vans and delivered to their final destination. the objective is to minimise total transport and tardiness cost. After restricting the routes in the disposition stage, we formulate a mixed-integer linear program that captures the entire delivery process. then, we propose a Benders' decomposition and prove the validity of a set of optimality cuts and of a subproblem relaxation. We show the impact of this approach on large-scale real instances under user-imposed time limits. We further strengthening the master problem with a set of valid inequalities and speed up the solution of the subproblem using constraintprogramming.
As for any decomposition method, the computational performance of a logic-based Benders decomposition (LBBD) scheme relies on the quality of the feedback information. therefore, an important acceleration technique in ...
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ISBN:
(数字)9783030782306
ISBN:
(纸本)9783030782306;9783030782290
As for any decomposition method, the computational performance of a logic-based Benders decomposition (LBBD) scheme relies on the quality of the feedback information. therefore, an important acceleration technique in LBBD is to strengthen feasibility cuts by reducing their sizes. this is typically done by solving additional subproblems to evaluate potential cuts. In this paper, we study three cut-strengthening algorithms that differ in the computational efforts made to find stronger cuts and in the guarantees with respect to the strengths of the cuts. We give a unified description of these algorithms and present a computational evaluation of their impact on the efficiency of a LBBD scheme. this evaluation is made for three different problem formulations, using over 2000 instances from five different applications. Our results show that it is usually beneficial to invest the time needed to obtain irreducible cuts. In particular, the use of the depth-first binary search cut-strengthening algorithm gives a good performance. Another observation is that when the subproblem can be separated into small independent problems, the impact of cut strengthening is dominated by that of the separation, which has an automatic strengthening effect.
In this paper we develop a memristive True Random Number Generator (TRNG) circuit into a recurrent neural network building block. We revisit the design of a memristive TRNG circuit and demonstrate how its ability to a...
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ISBN:
(数字)9798350308921
ISBN:
(纸本)9798350308938
In this paper we develop a memristive True Random Number Generator (TRNG) circuit into a recurrent neural network building block. We revisit the design of a memristive TRNG circuit and demonstrate how its ability to alter the mean-value of the generated bitstream, can also be exploited to construct a Stochastic Binary Neuron (SBN). Using experimental data, we verify the operation of the circuit as a SBN for a range of input voltages. We present the theory required to target practical optimisation problems and to incorporate the proposed SBN circuit into stochastic neural networks, such as Boltzmann Machines. Finally, we demonstrate via simulation, preliminary results on how neurons based on our experimental SBN results can be used in networks to represent boolean expressions.
Benefits of static type systems are well-known: they offer guarantees that no type error will occur during runtime and, inherently, inferred types serve as documentation on how functions are called. On the other hand,...
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